Postdoctoral Researcher in Vegetation Mapping and Herbivory - Greenland Institute of Natural Resources (GINR), Nuuk, Greenland

Postdoctoral Researcher in Vegetation Mapping and Herbivory - Greenland Institute of Natural Resources (GINR), Nuuk, Groenlandia - 40 hrs/semana - Trabajo de campo ártico con UAV y machine learning - Deadline 31 mayo 2026

Location: Nuuk, Greenland

Organization: Greenland Institute of Natural Resources (GINR)

Contract Type: Postdoctoral position

Main Description:
The Greenland Institute of Natural Resources is seeking a postdoctoral researcher to study herbivory and develop plant biomass maps in areas used by large herbivores (caribou and muskoxen). The position involves field measurements, UAV mapping, and AI-based analysis. Results will be used to advise the Government of Greenland on wildlife conservation and management.

Requirements:

• PhD in natural sciences
• Experience in plant ecology and large herbivore ecology
• Experience in ecological fieldwork in remote Arctic/subarctic environments
• Experience integrating field data with UAV mapping (multispectral, structure from motion, LiDAR)
• Experience applying machine learning (random forest, deep learning) to vegetation classification and biomass estimation
• Experience with Google Earth Engine or other remote sensing platforms
• Competence in quantitative analysis with R and/or Python
• Proficiency in spoken and written English
• Knowledge of Danish and Greenlandic is an advantage

Benefits/Conditions:

• Salary according to collective agreements between the Government of Greenland and organizations
• GINR assistance with accommodation according to internal regulations
• 40 hours per week
• Travel included for fieldwork and meetings

How to Apply:
Submit application, CV, diplomas, certificates and relevant documents through the online form at the job posting page. For more information contact Mathilde Le Moullec (malm@natur.gl, +299 244752) or Fernando Ugarte (feug@natur.gl).

Application deadline: May 31, 2026

More information and application

🌍 ¿Te interesan ofertas como ésta?

Cada semana envío una selección de las mejores oportunidades en biología, medio ambiente y conservación directamente a tu correo. Además, estrategias profesionales, cursos y noticias del sector para que estés al día.

Apúntate a las Biotapas

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Desarrolla tecnologías para un planeta sin deforestación trabajando con datos geoespaciales a gran escala

Oferta compartida por Cristina

Senior Software Engineer (Geospatial Data)

About Us

We are a fast-growing, Series A NatureTech company (backed by leading investors AzureX Space Ventures, Equinor Ventures, and Intercontinental Exchange) on a mission to enable zero deforestation and degradation and support mass forest restoration by producing the highest-quality nature mapping data and insights products.

Data is at the heart of Space Intelligence. We process large volumes of satellite data and analyse it within a machine learning framework to produce valuable nature mapping products for our clients.

Our products are trusted by the developers and investors in nature-based solutions, including Apple, Climate Asset Management, Everland, and WCS. They are also used to support the validation of compliance with the EU Deforestation Regulation (EUDR) through our partnership with ICE’s Commodity Traceability Service (COT).

We are a group of passionate, dedicated individuals with deep technical and scientific knowledge necessary for producing reliable, high-quality data and insights. We have a strong understanding of our customers’ needs and develop long-term relationships that add value.

We are a values-driven organisation, embodying these principles in our daily work: we are Science-driven, with a Commitment to Quality, always Acting with Integrity. We have a focus on Innovation to create better products for our clients and an overall commitment to Equality. We are striving to create a commercial culture that is meritocratic and outcome-oriented.


Purpose

Our Senior Software Engineers in the Pipelines Data team partner with our world class Mapping Science and research teams to create pipelines for large scale analysis of Satellite imagery (Gigapixels scale) using data manipulation and machine learning.

You’ll:Write ML and Data pipelines in python from scratch, with scientific input from the Science team.
Optimise (for performance, and maintainability) pipelines written by others.

Our Pipelines team splits their time between working in an engineering focused team, and embedding into our Science team, producing actual data, assisting them with big data engineering, and helping them optimise our pipelines.

This role is a leadership role involving providing technical leadership, and mentoring to the team.


Who the role reports to

One of our Software Engineering Managers, or Head of Engineering.


Key Responsibilities and Deliverables

Your top level responsibility is to develop, deliver and maintain high quality products. Key responsibilities within that will be as follows:Be a leader in the team, mentoring and training other team members, and stepping up to lead projects or delivery as needed. You’ll “lead by example” modelling good practice.
Deliver high quality, low defect, maintainable (well structured for extension, well designed, documented & tested) code and systems, working closely as part of the team.
Review other engineers’ code, with a focus on their development – using the opportunity to mentor and train them.
Debug and fix issues identified in testing or production. – inc. providing UK business hours support.
Lead and contribute to testing.

The above is not exhaustive. Within reason, and in discussion with the role-holder, we may amend from time to time and may also ask to carry out other tasks that we consider appropriate.


Key Qualifications, Requirements, CompetenciesAlthough you may not be a scientist by training, you’ll be keen to partner closely with Forest, Data and Remote sensing scientists, learning to speak their language. You’ll likely have either a strong academic background in Physical Science / Geospatial, or at least demonstrable interest in this area and be a quick learner.
You will have experience with dealing with big datasets, optimising performance and implementing scalable solutions.
(Desirable) Experience of Machine Learning for geospatial data or similar areas such as Computer VisionExtensive experience of software engineering, including design, implementation, Testing (manual and automated) and problem diagnosis. Typically 5+ years. – covering at least 1 of the team’s focus areas of (Geospatial)Data, DevOps or ML
A technical degree or equivalent experience – Software Engineering/CS/ML degree is a bonus but not required.
You’ll have taken ownership of the development of significant software products or components in a multi person team.
(Desirable) Significant experience of Scrum/Agile.
Our tech stack is as follows – knowledge of these is a bonus but not required. Azure
Terraform
Python
xArray and Dask
GitHub
We are looking for a candidate who will be based in our office in central Edinburgh. Most of our team are in the office most days, and we feel you will learn fastest if you are in the office most days too. However, we support hybrid working and would be happy for you to work 1-2 days a week from home.
Right to work in the UK


Salary

Starting salary range £50,000 – £70,000. Placing dependent on experience. Pro rata for part-time.


Key decisions this role-holder makesTechnical design decisions – e.g. infrastructure / library selection
Architectural decisions – proposing the appropriate architecture for a piece of software/infrastructure.
Prioritisation decisions – do we do X or Y first? Do we need to do Z before we release?

For all of the above – you’ll make smaller decisions independently, larger decisions you’ll drive, and agree with the team and other stakeholders, and the biggest you’ll make in collaboration with the Head of Engineering.


Company values

We have defined values and we are proud of them. Each team member has an obligation to work in a way that is in keeping with our values and this will form part of how we assess contribution to our business.

Our values are –Science Driven
Committed to Quality
Integrity
Innovation
Equality


Working hours

37.5 hrs full time. We also welcome applicants to do this role Part time, ideally 70%+. We are a family friendly employer and offer a degree of flexi-time.

All our roles operate within normal office hours, Mon – Friday. Very rarely, weekend and evening working may be required

Some travelling may be required – up to 10% of time for this role

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Especialista en GIS para trabajar en conservación con tecnología top, jornada de tres días semanales

 Oferta compartida por Cristina

We're seeking a GIS & Data Science Specialist

Join our team!


Could you be our next team member to help empower conservation through data and technology?


Connected Conservation Foundation is excited for a GIS and Data Science Specialist to join our small team, to help us design and support remote sensing projects. This is a unique opportunity to work with local conservation teams across the globe and technology experts in corporations such as Cisco and Airbus. You’ll help us join capabilities across partners to put technology to work for protected areas, people and wildlife.

Location: Based remotely in either: the UK, South Africa or Kenya
Contract: Two-year contract / Part Time (@ 3 days a week, with flexibility to increase)
Key Contacts: Sophie Maxwell, Executive Director
Salary: Commensurate with experience in GIS and Data Science, plus geographic location of applicant.
Benefits: Pension (@ UK minimum requirements). No health or relocation package.
Required: Please send your CV and Cover Letter to info@connectedconservation.foundation

You’ll work collaboratively with the Technical Leads from our partner conservation and corporate organisations, researching the best solutions and approaches for the design and support of appropriate conservation technology to meet conservation challenges. Working closely with field teams, you will develop use cases, align solution providers, understand the latest progress in geospatial projects and advise on implementation and enhancements.

This role requires a passion for wildlife conservation, sustainability and environmental stewardship, coupled with a strong affinity for innovative technologies, through research and the identification of potential funding opportunities that could enhance the work of our community-based field partners.

Proficiency in a range of technical competencies is essential, encompassing GIS, remote sensing, telemetry, machine learning and cloud technologies. Your daily responsibilities will encompass the creation, delivery and support of solutions within these domains.

Key Responsibilities:Build engagement with new partners to understand their project requirements and how CCF and our corporate partners can help.
Work with specialists across organisations to define problem statements, use cases and input into solution development.
Provide support to conservation organisations and scientists designing data collection, data analysis and interpretation of complex datasets to enable data-driven decisions.
Manage acquisition, collection, analysis and troubleshooting of GPS, GIS and remotely sensed data to support our partner’s projects and decision-making.
Bring a solid foundation and experience in managing, building and using machine learning and modelling pipelines.
Work to continually advance data analytics solutions and your own expertise. Staying abreast of new Machine Learning techniques and remote sensing approaches to address environmental challenges.
Manage CCF’s data infrastructure, software licensing, and data and GIS-related computing resources.
Review data collected from fieldwork and other projects and summarise data in reports, documents, presentations or other methods.
Work with our Communications and Fundraising Manager to produce visually compelling data visualisations and summaries for fundraising, grant proposals, donors and communications activities.
Communicate with local communities, field teams, rangers, technology partners and conservation stakeholders to determine needs and explain any technical issues.
Help field partners install any new technologies, access data and test new solutions.
Support and consultancy for conservation field teams on technical improvements, related to GIS, remote sensing and Data Analytics.
Help monitor and diagnose technology and equipment problems, helping to resolve issues.
Support training of users on best practices.
Log overseas donated equipment licences for conservation partners.

Qualifications:Bachelor’s or master’s degree in geoinformation, computer science, data science or a similar-related field.
At least two years of GIS and/or Data Science experience, ideally with both, in a professional capacity.
Experience with remote sensing analyses related to conservation and ecosystem change detection.
Experience managing and analysing complex datasets and databases.
Experience applying machine learning techniques to satellite imagery.
Excellent written and verbal communication skills with the ability to collaborate with diverse geographic and technical backgrounds.
Attention to detail, with excellent follow-up skills to see projects and research to completion.
Self-learner and self-manager, with a start-up inquisitive mindset who loves problem-solving.
Proficient in excel, word and esri/GIS products including ArcGIS.
Desirable is experience with drones for wildlife and ecosystem surveys.
Fluency in English.
This is not a post-graduate role.

About us

Connected Conservation Foundation is a small charity of three persons, achieving so much with our partners. We exist to protect and restore wildlife and natural ecosystems, supporting local education and communities through technology. By uniting the collective capabilities of local partners, technology leaders and conservationists, we apply digital solutions to solve local wildlife challenges and bring benefits to both wildlife and people. CCF has nine long-running projects across Kenya, South Africa and Zambia, with solutions to help stop poaching, environmental destruction and human-wildlife conflict.

Our 2030 goal is to use technology to multiply conservation capacity to protect and restore 10 million hectares of natural habitat, conserve 50+ threatened species and improve the lives of people living in local communities. We believe technology has a critical role in helping us reach the United Nation’s ambition to protect 30% of the planet by 2030.

APPLICATION DEADLINE: Monday 13 November, 2023
Interviews will take place in December 2023.

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Tres oportunidades de PhD en identificación de plantas mediante LiDAR y RGB en Suiza

Oferta compartida por Cristina

Tree Species Identification


Identifying tree species in RGB aerial images and terrestrial LiDAR using Deep Learning


Background

Global climate change is affecting ecosystem functions and the adaptive capacity of forests at an accelerating rate, therefore, it is essential to improve forest resilience. The basis for the above is an intimate knowledge of our forest ecosystems, including a timely, and effective monitoring of forest development. Hence, under a dynamic climate, monitoring species richness will be critical to designing policies that ensure the provision of ecosystem services.

 
Project aim

We will develop models and algorithms capable of accurately detecting tree species in the over-​ and understory of forests. Specifically, we aim to: 1) develop deep-​learning models based on high-​resolution remote sensing imagery for overstory tree species recognition; 2) assess the transferability of these models to larger scales; and 3) evaluate the capabilities of terrestrial laser scanning for understory sapling species identification.
Scientific and social context

In recent years, tree species mapping has become a hot topic among the scientific community and practitioners, driven by increasing awareness regarding the importance of maintaining forest resilience to extreme events. The outcome of this research will provide the first automatic tree species detection model that can be applied across geographic regions. The automatic species detection will serve as a basis for improved inventory planning, for the planning of forest operations, and to ensure targeted management activities for more resilient forests.
Project lead

Dr. Mirela Beloiu & Prof. Verena Griess, ETH Zurich

Collaborators:
Dr. Ionut Sandric, University of Bucharest
Dr. Nataliia Rehush, Swiss Federal Institute for Forest, Snow and Landscape Research WSL
Prof. Dr. Arthur Gessler, Swiss Federal Institute for Forest, Snow and Landscape Research WSL
Dipl. Ing. Peter Surovy, Czech University of Life Sciences Prague
Dr. Arnadi Murtiyoso, Forest Resources Management, ETH Zurich
Students:

Lucca Heinzmann, Cécile Reichmuth
Funding

Swiss National Science Foundation

COST Action: CA20118 - 3DForEcoTech - Three-​dimensional forest ecosystem monitoring and better understanding by terrestrial-​based technologies
Contact

Dr. Mirela Beloiu (mirela.beloiu@usys.ethz.ch)

Apply here

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Oferta muy interesante dirigiendo equipos en remoto. Especial para apasionados de la AI y el machine learning

Oferta compartida por Cristina

Director of Research

Full-time & Remote

Earth Species Project (ESP) is a non-profit organization focused on using artificial intelligence to advance our understanding of animal communication, and ultimately to decode non-human languages. We believe AI has the potential to transform the way we perceive the world around us, expanding the ability of human beings to learn from other species. Our hope is that this will make a significant contribution to altering human perspective on how we relate to the rest of nature.

ESP partners with biologists and machine learning researchers at leading universities and institutions around the world, and we are honored to be supported by many forward-looking philanthropists and groups including the National Geographic Society and the entrepreneur and author Reid Hoffman.

RESPONSIBILITIES

We are looking for a thought leader in artificial intelligence with a track record of managing a team of researchers. ESP is still growing and you will have the opportunity to shape our long-term research agenda.

You will work with biology and machine learning experts to create understanding from entirely new scopes. You have experience leading research teams in designing algorithms that find structure in labeled and unlabeled data (audio, video, text, accelerometer, and other modalities).

You will also help cultivate a team of AI researchers, and will play a key role in hiring, mentoring, and hands-on career development. ESP’s AI researchers are responsible for developing and applying techniques in machine learning, bioacoustics, and ethology, disseminating their work in scientific publications, and collaborating on these efforts with other members of the AI team as well as with external biology partners.

In addition to your scientific work, you will help support ESP’s fundraising efforts by reviewing proposals and providing information to funders, as well as supporting external relations by conducting media interviews and meeting with collaborators. You will be responsible for collaborating with the communications, impact, and executive leadership teams to ensure that our AI research is aligned with ESP’s mission and goals.

You will have the opportunity to work with partners at various institutions like Cornell University, Imperial College of London, University of Oxford, Massachusetts Institute of Technology, University of California Davis, University of California Santa Cruz, University of St. Andrews, Monterey Bay Aquarium Research Institute, Woods Hole Oceanographic Institute, the Internet Archive, and the Jane Goodall Institute.
YOUR BACKGROUND

We are open to traditional and non-traditional backgrounds.

Your areas of expertise might include: machine learning (deep learning, self-supervised learning, generative models, multimodal learning), natural language processing (unsupervised machine translation, language models), (computational) linguistics, bioacoustics, signal processing, data science, statistics, or mathematics.

Additionally, you have experience in the following:Management: You have a track record of attracting and retaining the best technical talent, growing and leading teams of researchers, and collaborating cross-functionally with leadership teams to advance the strategic AI roadmap and develop success metrics
Machine learning: You have an exceptional understanding of machine learning; knowledge in related fields (e.g., math, statistics, probability theory, computer science) is a plus
Research: You have conducted or led research projects and your work has been published in peer-reviewed journals

You might play a musical instrument, do long-distance running, enjoy teaching, knitting, wilderness trekking, or are an incredible parent. We’re excited about full human beings (and remain open to applications by qualified non-primates).
ESSENTIAL QUALITIESLeader who enjoys collaboration and working with others
Passion for ESP’s research areas of focus
Desire to advance the fields of biology and artificial intelligence
Good communicator, writer, and listener
Openness to feedback, willingness to learn, and curiosity
Creativity in your approach to problem solving
BENEFITSCompetitive pay
Medical insurance, dental insurance, and vision insurance - ESP covers 100% of the premium
401k plan with match (if based in the United States)
2,000 USD home office stipend
Unlimited paid time off, with a recommended minimum of three weeks per year
Flexible working hours
Collaborations with top biologists and conservation institutions in the field of behavioral ecology
Opportunity to observe and participate in data collection - previous research includes bioacoustic and behavioral ecology fieldwork in Alaska, Monterey Bay in California, and the Congo rainforest
Biannual team retreats around the world

We are a fully remote team and you can be located anywhere in the world. You will occasionally be expected to participate in virtual meetings outside of typical working hours in your time zone. Additionally, you must have the willingness to travel internationally (<20%) for events and in-person team gatherings. Earth Species Project has a dynamic, flexible, and fun working environment with many opportunities for learning and personal growth.

We are committed to equal employment opportunities regardless of race, color, religion, gender, gender identity or expression, pregnancy, sexual orientation, marital status, ancestry, national origin, genetics, disability, age, veteran status, and criminal history, consistent with legal requirements. We encourage folks of all backgrounds and perspectives to apply.

If you require any accommodations, please email us at jobs@earthspecies.org and we’ll work with you to meet your accessibility needs.

Apply here

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Varios puestos para trabajar en Pivotal

Current Openings


About Pivotal:


We are a team of ecologists and technologists who believe good business must be good for nature. We’re building an economy that puts nature and business in balance by incentivising the restoration of nature at scale.


Economies and societies around the world need our planet’s diverse plant and animal life to create the products and services we take for granted. Protecting and restoring nature is vital to the future of human life as we know it.


For the first time, investment into biodiversity regeneration is being prioritised. Financing is flowing to projects and start-ups that are creating practical, viable solutions. Governments, companies and individuals around the world now need affordable, scalable ways to link biodiversity commitments and actions to real, evidenced outcomes. That’s where we come in.


Our mission is to provide the data people and companies need to invest in positive outcomes for nature. We capture biodiversity data on the ground using a range of technologies. All the data we collect is organised and analysed first with machine learning, then quality-checked by ecosystem experts to provide measured, quality-controlled analytics to show evidence of any biodiversity gains on the ground. We can then link these measured gains to a variety of financial mechanisms – such as sustainability-linked bonds and biodiversity credits – enabling money to flow to those projects and activities that create the most positive change.



Data Engineer (Remote)

Electrical Engineer (Remote)

Full Stack Python Developer (Remote)

Machine Learning Researcher - Computer Vision (Remote)

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Varios puestos de asistente de investigación para análisis de datos de biodiversidad acústica

Oferta compartida por Cristina


Research Assistant positions available


The Kitzes Lab at the University of Pittsburgh is seeking several Research Assistants to contribute to analysis of acoustic biodiversity data sets. Our lab’s research focuses on understanding how human alteration of natural habitat impacts species abundance and diversity, motivated strongly by an interest in informing conservation and habitat management.

As part of this work, our group is deeply involved in the development and application of automated acoustic recording methods for studying biodiversity, particularly birds, at large spatial scales. Among other activities, we develop open source software and machine learning models for the automated identification of bird song and, with our networks of collaborators, deploy over a thousand automated acoustic recorders each field season throughout Pennsylvania and beyond.

The main responsibilities of these positions will include several or all of Assisting in the development and/or testing of acoustic recorder hardware
Managing large acoustic data sets collected by the lab
Creating and/or applying machine learning models to analyze data on local, cluster, and cloud hardware
Annotating audio for species presence
Using statistical modes to estimate occupancy and abundance of focal species
Interpreting the results of these analyses in manuscripts and other communications

The particular responsibilities of each Research Assistant will depend on their background and skills, as well as the needs of the overall team. In general, we will be looking for candidates with more than one of the following skillsProgramming experience (Python preferred, other languages acceptable)
Demonstrated interest or experience in training machine learning models
Experience with bioacoustics
Experience with field work
Ability to bird by ear in Eastern temperate forests
Record of first-authored peer-reviewed publications

The Research Assistants will be supported by a combination of funding sources, including the National Science Foundation, the Gordon and Betty Moore Foundation, and the National Fish and Wildlife Foundation.

We currently have openings for Research Assistants at the Research III level. These positions are appropriate for candidates with a Master’s degree, several years of work experience, and programming or statistical expertise. The Research III candidates will be expected to take a more independent role managing and completing research projects.

We are a highly collaborative and interactive lab group in which multiple lab members work together on all of our research projects. We make a specific point to involve all of our lab members in reading groups, manuscript writing, conference presentations, grant writing, and other activities.

To apply for these positions, please begin by sending an email to justin.kitzes@pitt.edu with (1) a cover letter describing your interest in this position, (2) a resume or CV, (3) the names of three references, and (4) a writing sample. Review of candidates is ongoing.

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Un postdoc de lo más interesante estudiando la evolución de las suturas craneales en mamíferos

Oferta compartida por Nuria

This post is funded by a Leverhulme Trust research grant focused on the evolution of cranial sutures through the synapsid to mammal transition. The mammal skull performs numerous critical functions, from prey capture and feeding to protecting the brain to fighting. These functions impose enormous pressures which are buffered by the skull's shock absorbers: cranial sutures. These highly variable joints between skull bones are intimately linked with ecology and development, but their complex 3D anatomy makes them tricky to capture using traditional methods. As a result, we know almost nothing about their evolution. Bridging imaging, machine learning, cranial function and evolution, this project will reconstruct suture evolution and its role in one of the most important events in the history of life: the rise of mammals. This post will be based in the Goswami Lab within the Science Group at the Natural History Museum in London, with project collaborators based at London South Bank University, the University of Liverpool, the Field Museum of Natural History, and North Carolina Museum of Natural Sciences.

The successful applicant for this post will be responsible for developing and analysing a 3D dataset of suture morphology spanning extant mammals and their extinct relatives back to the earliest synapsids. Working with another project PDRA who is developing machine learning and computer vision tools for the automated extraction of cranial suture morphology from 3D meshes, the successful applicant will lead delivery of the biological and evolutionary aspects of this project, including expanding an existing 3D scan dataset spanning hundreds of living and extinct synapsid (including mammal) species, continuing development of a training dataset for the AI pipeline by annotating sutures on 3D scans, and conducting phylogenetic comparative and macroevolutionary analyses of suture evolution through time, as it relates to key innovations in mammal evolution and diversification.

The successful applicant will be expected to travel to international collections to build the 3D dataset, work closely with all project team members and collaborators, including organising project meetings, and lead on scientific publications and conference presentations describing the evolutionary analyses, as well as promoting the project at various outreach events at the NHM and outside the museum as the opportunity arises. There will be opportunities for supervising students and for developing independent collaborations, as part of supporting career development of the successful candidate. We provide a friendly, flexible, and collaborative environment to accommodate and support diverse circumstances, backgrounds, and needs.

About you

The successful candidate will have a PhD in Evolutionary Biology or related subject, either completed or submitted by the time of starting this position. You should have familiarity with mammal evolution and cranial anatomy and experience with 3D data and models, morphometrics, and phylogenetic comparative analysis in R. You should be willing to travel to work with collaborators and collect data in international institutions. You should have a track record of presenting research at conferences and publishing in peer-reviewed journals, demonstrating strong communication skills. You will have the ability to work independently, but also as part of a team, including contributing to wider lab activities and discussions. You must demonstrate ability to complete a research project and be eager to lead research in new areas and with new methods. International applicants welcome, and funds are available to support visa costs and NHS surcharge.

How to apply

If that sounds like you, please apply online on the Natural History Museum's careers portal, at https://careers.nhm.ac.uk/ . Please include a full curriculum vitae and cover letter detailing your interest
and relevant experience.

Closing date: 9am, March 3
Interviews expected w/c March 13

For further information and any queries, please contact: Prof. Anjali Goswami, The Natural History Museum, Cromwell Road, London SW7 5BD UK; a.goswami@nhm.ac.uk; goswamilab.com

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Doctorado que incluye recoger datos acusticos y muestras de eDNA en el Amazonas para desarrollar un marco de monitoreo de biodiversidad

Oferta compartida por Cristina

PhD position Biodiversity co-benefits of large scale restoration in the Brazilian Amazon

Supervisors: Dr Cristina Banks-Leite (mailto:c.banks@imperial.ac.uk); Prof Rob Ewers, Life Sciences; Dr. William Pearse, Life Sciences; Dr. Renato Crouzeilles, Mombak 

Department: Department of Life Sciences 

Climate change and biodiversity loss dominate concerns over anthropogenic modification of the natural world. For the last 40 years, each decade has been successively warmer than the last; the most recent with global surface temperatures 1.09°C higher than before the industrial era. In addition to a changing climate, life on Earth is under extreme pressure from habitat change, invasive species, over-exploitation and pollution (Millennium Ecosystem Assessment, 2005). As a result, it has been estimated that 1 million species will likely go extinct in the coming decades, coinciding with declines in overall biomass (IPBES report, 2019). 

We are now seeing a strong push for the development of large-scale solutions to reduce atmospheric carbon dioxide levels and air pollution to mitigate climate change, while also reversing trends in biodiversity decline. One solution being increasingly promoted is reforestation, as it is likely one of the most effective strategies to sequester CO2, and the most effective strategy to mitigate biodiversity loss in tropical forest areas. Reforestation is however an umbrella term for many types of interventions that range from planting non-native trees in non-forested areas to restoring native habitat. In this project, we are partnering with Mombak, a start-up based in Brazil aiming to become the world’s largest company on carbon removal with highest integrity, starting by reforestation the Brazilian Amazon. Mombak aims to have about 100,000 hectares of Amazonian forest under reforestation within the next five years and within this setting we will ask the following questions: 

1) How do soundscapes change through time and does landscape and regional features and planting scheme affect this trajectory? 

2) Are ecological trends revealed by acoustic monitoring similar to those obtained by environmental eDNA? 

3) What spatial and temporal environmental factors drive alpha, beta and gamma diversity? 

This project includes a field season in the Amazon to collect acoustic data and samples for eDNA analyses. Student will use machine learning to process acoustic data to calculate changes in acoustic composition and variation in acoustic diversity across the diel cycle. Student will also perform ecological analyses to compare acoustic data to eDNA, which will be sequenced by commercial partners. The outcome of this project will both aid Mombak to develop a cutting edge biodiversity monitoring framework for the carbon market and will drive forward the knowledge on biodiversity recovery in reforested areas.

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Identifica comportamientos de águila real aplicando técnicas de machine learning

Oferta compartida por Cristina

Movement and behavioural ecology of juvenile golden eagles

Outline

Golden eagles (Aquila chrysaetos) are among the most charismatic birds of the alpine environment. Yet due to their high mobility and their remote occurrence, large aspects of their lives remain elusive. Tagging juvenile golden eagles with the newest generation of GPS and tri-axial accelerometer (ACC) tags allows us to bring together individual space use, habitat characteristics and specific behaviours.

Research aims

The present MSc project will investigate the behaviours of juvenile golden eagles across space and time and asses their drivers and potential consequences.

Methods

The candidate will apply a ground-truthed machine learning algorithm for identifying golden eagle behaviours onto an extensive database of accelerometer-data of ca. 80 juvenile golden eagles. This will allow assessing the abundance and composition of specific behaviours in space and time. Relating these to different intrinsic and environmental factors, as well as individual performance, will allow to infer about proximate and ultimate drivers and consequences of these behaviours. The results of this thesis shall be published in a high-quality scientific journal. The project will be embedded in an ongoing PhD-project (ETHZ/Swiss Ornithological institute) and a multinational Alpine golden eagle project led by Max-Planck Institute for Animal Behaviour. The MSc thesis will not involve any fieldwork. However, visiting the study area and potentially joining a golden eagle tagging event may be possible.

Requirements

Background in biology, environmental sciences, geographical sciences or similar. Strong interest in investigating ecological questions. Experience with R statistical language. Interest in learning and applying machine learning methods, working with large datasets and the analysis of movement data. Very good knowledge of English language and scientific writing. Knowledge of bird and raptor biology will be an advantage.

Contact

Dr. Matthias Tschumi
Swiss Ornithological Institute, 6204 Sempach
email: matthias.tschumi@vogelwarte.ch
Tel: + 41 41 462 99 24

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Si siempre has soñado con descubrir nuevas especies (de artrópodos), echa un vistazo a esta oportunidad en Berlin.

Oferta compartida por Nuria

3 tenure-track research positions with a focus on species discovery and taxonomy of hyperdiverse arthropod clades at the Center for Integrative Biodiversity Discovery, Museum fuer Naturkunde (MfN) Berlin, Germany
https://jobs.museumfuernaturkunde.berlin/jobposting/067dbdb4c8bb8cd36a232c28a9627486a3687b6a

The opportunity:
The Museum fuer Naturkunde Berlin has an internationally visible Center for Integrative Biodiversity Discovery. It will meet the scientific and societal challenges arising from rapid worldwide ecosystem change, not least the global biodiversity crisis, and capitalise on the chances and innovations from biodiversity. The Center will develop new scientific approaches to the study of biodiversity that will contribute to a more efficient and significantly faster global biodiversity inventory. At the same time it will enable high-quality taxonomic research on extinct and recent organisms and develop targeted knowledge products for various
user groups.

We are seeking three talented and motivated biodiversity researchers (f/m/d) with a focus on methods to develop and support the new Center for Integrative Biodiversity Discovery at the Museum fuer Naturkunde Berlin Leibniz Institute for Evolution and Biodiversity Science. To this purpose, the successful candidates will take a leading role in the development of innovative methods for species discovery and apply them to the taxonomy of hyperdiverse arthropod clades. The research should be embedded in the program of the Center for Integrative Biodiversity Discovery and involve engagement in grant applications as well as training and supervision of students and junior researchers. We also expect active participation in public outreach activities of the museum about biodiversity and biodiversity discovery. A particular focus of the Center is to develop new ways for the automatic discovery and description of species. For this purpose we combine biodiversity robotics with DNA barcoding and machine learning so that invertebrates can also be automatically identified by image in the future (see https://www.science.org/news/2021/06/artificial-intelligence-could-help-biologists-classify-world-s-tiny-creatures).

The Museum fuer Naturkunde Berlin provides an excellent research environment. It houses state-of-the-art laboratories for morphology (including histology, imaging, SEM, and CT labs), molecular genetics/genomics and computation. Numerous research groups are working in a wide range of research fields including population genetics, phylogenetics, developmental and evolutionary genetics, and taxonomy. Our world-class zoological collections provide unique access to specimens collected over the last 200+ years.

Requirements:

• PhD or PhD candidate in zoology with a significant publication record in collection-based biodiversity research on hyperdiverse terrestrial or limnic arthropod clades that are ideally dark taxa (clades where <10% of all species are described and the estimated diversity is >1000 species). 
• The successful candidates must have described new species in dark taxa and should have experience in developing innovative research approaches to taxonomy that combine high-throughput sequencing and morphological data. 
• Demonstrated experience in working on international research projects and obtaining third-party funding. 
• Field work experience, preferably also in larger collaborative projects and willingness to participate in research in one of MfN's geographic focus regions (e.g., Southeast Asia, Africa) are expected. 
• Successful candidates will be expected to work in an interdisciplinary environment at Germany's largest natural history museum. Excellent team player, proven communication skills and intercultural competence. 
• Professional written and verbal communication in English.

Application procedures:
We look forward to receiving your application with the usual documents (cover letter, curriculum vitae, certificates) as well as a statement (one page max.) outlining plans for research at MfN by 31.01.2022, preferably via our online application portal.

In support of equal rights applications from qualified women are particularly welcome. Handicapped individuals will be given preference in cases of identical qualifications.

For information on the application procedure, please contact recruiting@mfn.berlin

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Empieza tu propio grupo de investigación en biodiversidad y evolución en el Museo de Historia Natural de Suecia

Oferta compartida por Nuria


The Swedish Museum of Natural History (NRM) is hiring a tenure-track researcher in Data-Driven Life Science (DDLS), within the field of biodiversity and evolution. The appointed researcher will receive a start-up package of 17 M SEK, which includes funding to establish their own independent research group.

The NRM (www.nrm.se) is a major research institute with state-of-the-art equipment and dedicated laboratories that enable high-quality research on a broad range of natural history topics. The museum is located in Stockholm, which by many is regarded as one of the most beautiful capitals in the world, and is home to a vibrant scientific community with several leading research institutes, including the world-leading research infrastructures at the Science for Life Laboratory, nearby Stockholm University and the Royal Institute of Technology.

The research position is funded by the SciLifeLab and Wallenberg National Program for Data-Driven Life Science (DDLS), which is a 12-year initiative funded with a total of 3.1 billion SEK from the Knut and Alice Wallenberg Foundation (for more details, see www.scilifelab.se/data-driven). The DDLS Fellows will be recruited as independent group leaders at the respective host institution, and will have the opportunity to link up with other local research groups as well as the within the national DDLS programme.

Each DDLS Fellow will receive a recruitment package of 17 MSEK, which is meant to cover 5 years of his/her own salary, two PhD students andtwo postdoc positions, as well as running costs. The Fellow positions are tenure-track, and the universities/organizations will assume the long-term responsibility of their support as tenured faculty.


RESEARCH TOPIC

DDLS in biodiversity and evolution concerns research that takes advantage of the massive data streams offered by techniques such as high-throughput sequencing of genomes and biomes, continuous recording of video and audio in the wild, high-throughput imaging of biological specimens, and large-scale remote monitoring of organisms or habitats. This research subject area aims to lead the development or application of novel methods relying on machine learning, artificial intelligence, or other computational techniques to analyze these data and take advantage of such methods in addressing major scientific questions in evolution and biodiversity.

More specifically, at the NRM this research will be aimed at developing a deeper and dynamic understanding of biodiversity and ecosystem change, and to enable predictions on environmental change on global and local ecosystems. The scientific topics comprise the development and evolution of life, biodiversity, human evolution, environmental research or landscape ecology. From a methodological perspective, examples of such research include analyses of large-scale data within phylogenetics, population genetics or metagenomics, as well as image analysis or research on morphological and distributional data.


ELIGIBILITY AND ASSESSMENT

In order to qualify for the DDLS Research Fellowship, the applicant must have completed a doctoral degree in Sweden or an equivalent degree from another country. The position is primarily aimed at applicants who have received such a degree no more than eight years before the deadline for applications.

Since the DDLS Fellowships are aimed at early career researchers, having completed a PhD degree within the last eight years will constitute an important merit. During the selection process, special attention will also be given to research excellence within the field of DDLS in biodiversity and evolution. The applicants will also be evaluated on the basis of the planned research within the subject field, as well as experience in leadership and student supervision and track record in obtaining research grants.


TERMS OF EMPLOYMENT

The candidate will be employed as researcher until further notice, but no longer than five years. The contract may be extended under special circumstances, such as due to sick leave or parental leave. The successful DDLS candidate will be offered the choice to be employed at the department within the museum that best fits the candidate’s research profile. The museum’s life science departments are Bioinformatics and Genetics (BIO), Botany (BOT), Environmental Research and Monitoring (MFÖ),
Palaeobiology (PAL) and Zoology (ZOO).

The DDLS Fellows at NRM will, upon a successful evaluation of their project, be offered the opportunity for their employment to be transformed into a permanent researcher position financed by NRM. Researchers employed at the NRM, including DDLS Fellows, also have the opportunity to apply
for promotion to full professor


HOW TO APPLY

Applications should be submitted no later than September 5th, 2021, through the NRM recruitment portal. The recruitment portal and full instructions for applicants is available through this link:
https://www.nrm.se/vacancies

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¿Quiéres saber más sobre tus antepasados vikingos? Aquí tienes un postdoc estudiando el origen del genoma vikingo

Oferta compartida por Nuria

Lund University was founded in 1666 and is repeatedly ranked among the world’s top 100 universities. The University has 40 000 students and more than 8 000 staff based in Lund, Helsingborg and Malmö. We are united in our efforts to understand, explain and improve our world and the human condition.

The Faculty of Science conducts research and education within Biology, Astronomy, Physics, Geosciences, Chemistry, Mathematics and Environmental Sciences. The Faculty is organized into nine departments, gathered in the northern campus area. The Faculty has approximately 1500 students, 330 PhD students and 700 employees.

Dr. Eran Elhaik led the compositional genomic analyses in over a dozen sequencing consortia, whose results were published in Science, Nature, PNAS, and Genome Research. Dr. Elhaik lab is famous for its population genomics and biogeographical research http://www.eranelhaiklab.org/and collaborates with hundreds of researchers from all over the world.

Postdoctoral fellow in Computer science or computational biology: Developing Machine learning tools to analyze the origins of Viking genomes

Subject description
Ancient DNA (aDNA) has changed the studies of history, enabling us to directly analyze early genetic variation. In recent years, there has been a sharp increase in the amount of collected aDNA and high-profile studies, but insufficient information about the timing and geographical origin has limited the usefulness of the collected data and resulted in many erroneous reports. The project aims to develop machine learning tools to predict the origins of the DNA material. The methods will be used to reconstruct the origin of Scandinavian Vikings. The candidate will work jointly with Dr. Eran Elhaik, Dr. Patrik Eden, and Prof. Eske Willerslev (at the University of Copenhagen) to develop statistical methods for paleogenomics.

Work duties
We aim to develop Machine Learning methods that date and biolocalize ancient genomes with application to Viking genomes and answer questions about their mysterious origins and whereabouts.
This is a multi-disciplinary project involving programming and modeling. In addition, the project will involve collaborations with researchers in other disciplines, including biomathematics, biostatistics, and molecular biology. The candidate is expected to have a strong grounding in programming in R and math/statistics.
The main duty involved in this position is to conduct research. Teaching may also be included, but up to no more than 16% of working hours. The position shall include the opportunity for three weeks of training in higher education teaching and learning.
The successful candidate will work on the above-outlined research projects. It is expected that she/he will actively and creatively develop and optimize the detailed methods to pursue the overall project goals and, after a training period, independently analyze genomic data using machine learning and other statistical methods
All work will be carried out embedded in a collaborative research team, requiring sharing of expertise, open discussion of results and facilitating experiments of other team members
Active participation at international conferences is expected, as well as dissemination of results in peer-reviewed publications
Opportunities for the supervision of degree projects (Bachelor and Master) as well as co-supervision of Ph.D. projects may be provided
The successful candidate is expected to actively seek independent research funding during the employment period, providing the opportunity to transition towards an independent researcher position
Finally, the position may include limited duties in administration related to the work duties listed above

Qualification requirements
Appointment to a postdoctoral position requires that the applicant has a Ph.D., or an international degree deemed equivalent to a Ph.D., within the subject of the position, completed no more than three years before the last date for applications. Under special circumstances, the doctoral degree can have been completed earlier.
Qualified must have training in mathematics, biostatistics, or statistical genetics and experience in analyzing large datasets. Candidates are also expected to have fundamental knowledge and experience with Machine Learning methods. Candidates are expected to have an interest in biology and human history. The candidate must have a degree in mathematics, biostatistics, statistical genetics, or a similar relevant subject and experience of conducting such research through a previous research assistant post or working towards a Ph.D. Applicants must have the ability to collaborate well and communicate scientific materials to non-scientists.

Additional essential requirements:

• Very good oral and written proficiency in English.
• Excellent programming skills in Python/R or a similar language
• Strong statistic skills and experience with ML methods.
• Knowledge of common ML frameworks
• Experience in analyzing qualitative and quantitative NGS data
• A track record of publishing peer-reviewed academic papers
• Evidence of ability to work effectively both independently and as a member of a small team.
• Evidence of ability to organize resources, plan and progress work activities, and meet deadlines effectively and consistently
• Experience in adapting their own skills to new circumstances

Assessment criteria and other qualifications
This is a career development position primarily focused on research. The position is intended as an initial step in a career, and the assessment of the applicants will primarily be based on their research qualifications and potential as researchers. Consideration will be given to qualified candidates with good collaborative skills, drive, and independence.

Terms of employment
This is full-time, fixed-term employment of 2 years. The period of employment is determined in accordance with the agreement “Avtal om tidsbegränsad anställning som postdoktor” (“Agreement on fixed-term employment as a postdoctoral fellow”) between Lund University, SACO-S, OFR/S and SEKO, dated 4 September 2008.

Instructions on how to apply
Applications shall be written in English and be compiled into a PDF-file containing:

• Cover letter (your background, why are you interested in the position, and in what way the research project corresponds to your interests and educational background, your goals, and start date)
• Résumé/CV, including a list of publications
• A general description of past research and future research interests (no more than three pages)
• Contact information of at least three references
• Copy of the doctoral degree certificate and grades for the Ph.D., MSc, and BA studies

Candidates who satisfies the requirements would be further evaluated on programming and writing skills and, if successful, be invited for an interview.

To apply visit the original advertisement

Lund University welcomes applicants with diverse backgrounds and experiences. We regard gender equality and diversity as a strength and an asset. We kindly decline all sales and marketing contacts.

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Doctorado chulo mapeando arrecifes de coral con tecnología biofriki

The Max Planck Institute for Marine Microbiology is a research institute of the Max Planck Society. It was founded in 1992 in the State of Bremen and employs around 200 staff members. In close collaboration with numerous university and non-university research institutions, we explore the diversity and function of microorganisms in the ocean and their interactions with their environment. Scientists from all over the world, engineers, technicians and administrative staff together make an important contribution to global marine and environmental research.
In the Microsensor Group we are searching for a
PhD Student on Coral Reef Mapping


Framework
As a part of the EU-funded Training Network project “4D-REEF: Past, present and future of turbid reefs in the Coral Triangle”, 15 early-stage researcher (doctoral candidate) positions are available. The project consortium of 17 research institutes and universities will provide an excellent foundation for career development in reef studies, with local and international links, collaborative projects and an exciting training program.


Project: Habitat structure and spatial ecology in modern turbid reefs
The benthic dimension of reef habitats sets the stage for a complex set of interactions between biogeochemical processes, hydrodynamics, habitat competition and pelagic communities. Therefore, a comprehensive description of the reef benthos in terms of community composition, coverage and structure, is a key target of reef surveys. Using novel underwater hyperspectral surveying systems (HyperDiver), rich snapshots of the reef can be easily acquired. With the use of machine learning and image analysis, detailed habitat structure maps can be efficiently created. The dense reef biodiversity maps opens up the reef mesoscale to seascape-style analyses.

Objectives:

Establish methods and protocols for hyperspectral surveying of the seafloor in turbid or light-limited regions.

Development of computational pipelines for generating classified reef maps, exploring the use of modern machine
learning techniques

Derive metrics of reef health from survey data which can be validated against other measured ecological indices for pigmentation, bleaching, calcification.

Detailed study using chemical & optical microsensors of the status and role of key reef players (turf algae, calcifiers, etc.)


What we expect from you:

Experience in computational research and programming, esp. machine learning, neural networks and image analysis

A Masters degree in a relevant field of natural sciences or information & computing technology

A Strong motivation for marine ecological studies, preferably with experience of field work

A SCUBA diving certification, preferably Rescue Diver level

A strongly inter-disciplinary outlook and good written and oral communication skills

Experience with any of the following points of advantage: software/web development, ecological field work, biogeochemical analyses

Able to attend interviews and start the position soon after the application deadline



What we offer:

We offer a 3 year full-time appointment. Candidates can be of any nationality, but in order to be eligible for the EU-funded positions the following criteria applies to all applicants:

At the time of recruitment the applicant shall be in the first four years of his/her research career (eg. since completing Masters) and have not been awarded a doctoral degree.

The applicant must not have resided or carried out his/her main activity in the country of the host institute for more than 12 months in the 3 years immediately prior to the recruitment.

Applications must be submitted online. The deadline is August 25, 2019. For further information please contact Dr. Arjun Chennu (achennu@mpi-bremen.de) and see project website: https://www.naturalis.nl/en/4d-reef


The Max Planck Society is committed to employing more disabled individuals and especially encourages them to apply. The Max Planck Society strives for gender and diversity equality. We welcome applications from all backgrounds.

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