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Research assistant in diffusion modelling for terrestrial prediction(fixed term/part-time)

Cambridge
Permanent
University of Cambridge Vet School
Research assistant
Posted: 2 February
Offer description

Position Overview

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

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

We are an academic department that encompasses computer science together with many aspects of engineering, technology and mathematics. We have a worldwide reputation for academic research with consistent top research ratings. Our culture is open and collaborative, supporting revolutionary fundamental computer science research, strong cross‑cutting collaborations internally and externally, and ideas which transform computing outside the University.


Part‑time Research Assistant – Professor Anil Madhavapeddy

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 contribute to the work performing predictions in TESSERA's compact 128‑dimensional embedding space rather than on raw imagery.

The project explores whether we can:

* reduce computational costs,
* learn more stable temporal dynamics from semantically meaningful features,
* generate probabilistic forecasts with calibrated uncertainty,
* produce predictions directly usable for downstream tasks.


Qualifications

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.


Compensation

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


Application

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


Equal Opportunities

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

All employees must be eligible to live and work in the UK. We provide support for visa applications (if required) and will reimburse the cost of the first visa.

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