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University of Edinburgh

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Postdoctoral Research Associate in Reliable Constrained Generation with Large Language Models and Biological Data University of Edinburgh in United Kingdom

Degree Level

Postdoc

Field of study

Computer Science

Funding

Full funding available

Deadline

Aug 28, 2026

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Country

United Kingdom

University

University of Edinburgh

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Keywords

Computer Science
Biomedical Engineering
Biology
Mathematics
Probabilistic Modeling
Statistics
Large Language Models
Machine learning

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About this position

The University of Edinburgh is advertising a Postdoctoral Research Associate position in the School of Informatics, working with the April Lab on reliable constrained generation with large language models, neuro-symbolic AI, and applications to biological data.

The project is supervised by Dr Antonio Vergari and carried out in collaboration with Prof. Wouter Boomsma from the University of Copenhagen. The research focus is on principled probabilistic methods for controlled generation with LLMs, aiming to improve reliability and efficiency while testing the approach on sequential biological data.

This is a 2-year fixed-term postdoctoral role, full-time at 35 hours per week, graded UE07, with salary £41,064-£48,822 per annum. The post includes funding for international conference travel and access to HPC infrastructure. The university states that the role is open to UK and international applicants, with visa sponsorship available.

Applicants should be prepared to contribute to cutting-edge research in machine learning, probabilistic modeling, and neuro-symbolic systems, assist with biological-data applications, and write and present scientific papers. The application requires a CV, a 1-page cover letter, a 2-page research statement aligned with the April Lab, and a list of three relevant papers plus a link to a maintained codebase. Incomplete applications will be desk rejected.

The closing date is 28 August 2026. Interviews will be held on a rolling basis. The position is based in Edinburgh, United Kingdom (hybrid working mentioned).

Funding details

Full funding including tuition fees and living expenses is available for this position. The scholarship covers all educational costs and provides a monthly stipend.

How to apply

Please submit your application including a cover letter, CV, academic transcripts, and contact information for two references. Applications should be sent via the online portal before the deadline.

More information can be found here

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