Al final me voy a terminar mudando a Ciudad del Cabo: otra oferta interesantísima para jugar con datos durante la semana e irte de safari los findes ~ Bioblogia.net

1 de diciembre de 2020

Al final me voy a terminar mudando a Ciudad del Cabo: otra oferta interesantísima para jugar con datos durante la semana e irte de safari los findes

 



RESEARCH OFFICER (3-year contract) 

Centre for Statistics in Ecology, Environment and Conservation DEPARTMENT OF STATISTICAL SCIENCES FACULTY OF SCIENCE  

The centre for Statistics in Ecology, Environment and Conservation (SEEC, www.seec.uct.ac.za) in the Department of Statistical Sciences, University of Cape Town, is looking for a Junior Research Fellow to pursue a research programme at SEEC for three years. 

Possible research focus areas include: 

Impact of climate change on biodiversity. 
Understanding the effect of climate change on biodiversity is a key research theme at SEEC. We have long-standing expertise and strong international collaborations in population ecology, occupancy and species distribution modelling, functional ecology and macroecology. 

Data pipelines. 
With the ever-increasing availability of exciting new data streams, there is a huge need to establish transparent and reproducible workflows that extract decision-relevant information from raw data based on rigorous statistical analyses. SEEC has made a strategic decision to invest in this area, and we have established a partner network that includes the people who collect the data and those who inform decision and policymakers. We are particularly excited about the prospect of using these pipelines for near-term ecological forecasting. Examples include pollen forecast in collaboration with UCT’s lung institute, and bird population trends for SANBI and the Department of Environment, Forestry and Fisheries. 

Environmental decision-making. 
With the increasing human footprint, there is an increasing need to base environmental decisions on evidence and a transparent decision-making process. SEEC has experience with population assessments, habitat classification and also with Structured Decision-Making tools that take into account stakeholders’ values. 

Machine learning in ecology.
 Ecological data often take the form of images, audio, or video recordings that need to be annotated to be used in scientific research. As the amount of ecological data collected in this way increases, manual annotation is becoming a major bottleneck for research. Our machine learning research is developing computer-assisted approaches to facilitate the labelling of ecological datasets. The next step will be to combine machine-learning algorithms with statistical modelling, e.g. with the models we have developed for acoustic monitoring of animals or with time-series models of remote-sensing data. Other research programmes that fall within SEEC’s research ambit will also be considered. The successful candidate could either be a statistician with an interest in ecology / environmental science, or an ecologist / environmental scientist with strong quantitative skills. 

Requirements: 

• A PhD in quantitative biology, statistical ecology, or related discipline; and relevant post PhD research experience (minimum two years but exceptions can be considered);
• Track record of independent research that has led to publications in high-standing journals; 
• Strong data analysis skills using the R statistical environment; 
• Ability and commitment to working as part of a diverse team; 
• Excellent leadership and communication skills; and 
• Track record or potential in raising funds. 

The annual award is R658 000 (for up to three years) that will cover salary plus computing and research expenses. Split is negotiable. 

To apply, please e-mail the below documents in a single pdf file to Ms Natasha Khan at recruitment06@uct.ac.za 

• UCT Application Form (download at http://forms.uct.ac.za/hr201.doc
• Cover letter and Curriculum Vitae (CV) including publication list 
• Statement of research interests and proposed research programme that you will follow if you are the successful candidate 

Please ensure the title and reference number are indicated in the subject line. 
An application which does not comply with the above requirements will be regarded as incomplete.

Telephone: 021 650 3469 
Reference number: E200346 

Closing date: 18 December 2020 

UCT is committed to the pursuit of excellence, diversity and redress in achieving its equity targets. 
Our Employment Equity Policy is available at http://www.uct.ac.za/downloads/uct.ac.za/about/policies/eepolicy.pdf 

UCT reserves the right not to appoint.  

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