Research Assistant in Diffusion Modelling for Terrestrial Prediction

Department/Location: Department of Computer Science and Technology, West Cambridge 

Fixed-term: The funds for this post are available for 3 years in the first instance. 

Part-time: 10 hours per week (27% FTE) 

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. 

A part time Research Assistant position is available to work with Professor Anil Madhavapeddy in the Department of Computer Science and Technology at the University of Cambridge. 

The Research Assistant will play an active role in a project investigating temporal forecasting directly in latent spaces using diffusion models and/or normalising flows. Traditional Earth observation forecasting operates on high-dimensional raw satellite data, making it computationally expensive and noise-sensitive. The post holder will participate in scientific research, engineering software, and by contributing to the work performing predictions in TESSERA's compact 128-dimensional embedding space rather than on raw imagery. The project explores whether we can: (1) reduce computational costs, (2) learn more stable temporal dynamics from semantically meaningful features, (3) generate probabilistic forecasts with calibrated uncertainty, and (4) produce predictions directly usable for downstream tasks. 

Candidates will have experience in industrial machine learning and systems programming. An MPhil in Computer Science, or equivalent experience, is also essential. Further information about the criteria for the role can be found in the further particulars. 

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 'Apply' above.

Please quote reference NR48631 on your application and in any correspondence about this vacancy. 

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

The University has a responsibility to ensure that all employees are eligible to live and work in the UK.  Please note that we provide the support of applying for the relevant visa (if required) and will reimburse the cost of the first visa.

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