Research Assistant/ Associate (Fixed Term)

Fixed-term: The funds for this post are available for 12 months in the first instance.

The successful candidate will be based in the Department of Computer Science and Technology and will join the research group of Prof Emily Shuckburgh, as well as being part of the Centre for Landscape Regeneration (CLR).

The CLR is an ambitious programme of research that aims to provide the knowledge and tools needed to regenerate the British countryside using cost-effective nature-based solutions that harness the power of ecosystems to provide broad societal benefits including biodiversity recovery and climate mitigation and adaptation. The CLR focal landscapes are the East Anglian Fens, the Cairngorms, and the Cumbrian Lake District. The Research Assistant/ Associate will work in partnership with colleagues from multiple departments within the University of Cambridge as well as the collaborating organisations (RSBP, NIAB and UKCEH).

The role holder will investigate machine-learning approaches that advance the core objectives of the project by identifying optimal land management solutions to balance food production, greenhouse gas emissions reduction, nature conservation, and economic co-benefits. This will involve developing a collection of spatially distributed models for these objectives within an encoder-decoder framework to reduce the dimensionality, enabling the use of multi-objective optimisation to generate a wide range of optimal scenarios and explore trade-offs affecting decision-making.  A secondary goal will be developing a methodology to encode spatial constraints into latent space, ensuring only physically viable solutions are generated. The role holder will develop their approaches for one CLR landscape but with a view to applying it across all three. They will be expected to engage with relevant stakeholders to ensure their needs are incorporated. The ultimate ambition is to create interpretable frameworks and decision-support tools for decision makers and the role holder will be expected to lay the foundations for this.

The ideal candidate should hold a PhD in a relevant specialist subject or is about to submit, or should have equivalent experience. A background in machine learning applied in an environmental science domain is essential, with a track record of research publications commensurate with stage of academic career.

Appointment at Research Associate level is dependent on having a PhD. Those who have submitted but not yet received their PhD will be appointed at Research Assistant level, which will be amended to Research Associate once the PhD has been awarded.

The Department of Computer Science and Technology is an academic department that encompasses computer science along with many aspects of engineering, technology and mathematics. We have a worldwide reputation for academic research with consistent top research ratings. The Department has an open and collaborative culture, supporting revolutionary fundamental computer science research, strong cross-cutting collaborations internally and externally, and ideas which transform computing outside the University. Please follow the link at: https://www.cst.cam.ac.uk to find out more about our department. 

In addition to the base salary stated above, the successful candidate for this post will receive an additional 2.5% supplement to their pay.

To apply online for this vacancy and to view further information about the role, please click the 'Apply' button above. 

Please provide a CV and covering letter. If you upload any additional, unrequested documents, they will not be considered as part of your application.

The University actively supports equality, diversity and inclusion and encourages applications from all sections of society.

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