Research Associate

The University of Edinburgh; Easter Howgate; On-site; GBP 41,064 - 48,822; Full time

Benefits offered by this job

International travel funding

Access to compute infrastructure

Comprehensive staff benefits including generous annual leave

Job summary

A prestigious educational institution based in Scotland is offering a full-time Postdoctoral Research Associate position in machine learning. The role involves conducting innovative research, collaborating with industry partners, and contributing to pioneering projects. Candidates should have a PhD (or near completion) in machine learning or a related field, along with modern toolchain proficiency. The position promises a competitive salary, funding for travel, and an inclusive work environment.

Qualifications

• Research experience in probabilistic machine learning or diffusion/flow-based models.
• A track record of high-quality publications.
• Strong software engineering practices.

Responsibilities

• Conduct methodological research in machine learning.
• Collaborate with leading universities and industry partners.
• Explore real-world problems in collaboration with Hub partners.

Skills

Machine Learning

AI

Statistics

Applied Mathematics

Modern ML toolchains (e.g., PyTorch, JAX)

Excellent communication skills

Education

PhD (or near completion) in a relevant field

Tools

PyTorch

JAX

Job description

Grade UE07: £41,064 - £48,822 per annum

College of Science and Engineering / School of Informatics

Full-time: 35 hours per week

Fixed-term: for 24 months

The Opportunity

We invite applications for a Postdoctoral Research Associate in machine learning based in the School of Informatics, University of Edinburgh. The postholder will also be formally affiliated with the EPSRC-funded Hub in Generative AI and work with Drs Siddharth N. and Michael Gutmann as part of the Hub. This is an outstanding opportunity to conduct methodological research at the frontier of machine learning and to collaborate across a vibrant national network of leading universities and industry partners.

The scope of the project will be defined together with the candidate and tailored to their strengths and interests but will broadly focus on one or both of the following topics:

• Mutual information estimation and maximisation for continuous and discrete variables, with application to cross-modal data analysis or experimental design and active learning. This work stream will build on papers [1, 2].
• Probabilistic latent variable modelling with hierarchically structured continuous and discrete variables for more efficient and effective generative modelling [3,4] and uncertainty quantification, with application to diffusion models [5].

The overarching goal is to advance methodology and to explore their use in real-world problems in collaboration with Hub partners.

1. Neural Mutual Information Estimation with Vector Copulas, NeurIPS 2025 (https://openreview.net/forum?id=FYbe7r0mxu)
2. Implicit Deep Adaptive Design: Policy-Based Experimental Design without Likelihoods, NeurIPS 2021 (https://arxiv.org/abs/2111.02329)
3. Autoencoding Conditional Neural Processes for Representation Learning, ICML 2024 (https://proceedings.mlr.press/v235/prokhorov24a.html)
4. Banyan: Improved Representation Learning with Explicit Structure, ICML 2025
5. On Designing Diffusion Autoencoders for Efficient Generation and Representation Learning. (https://arxiv.org/abs/2506.00136v1)

The position includes funding for international travel, e.g., for attending conferences, visiting research collaborators, and disseminating research findings. The researcher will have access to the compute infrastructure available to the School of Informatics and the AI Hub.

We welcome both local (UK‑resident) and international applicants. We warmly welcome qualified candidates from all backgrounds to apply and particularly encourage applications from under‑represented groups in the field. We are strongly committed to offering everyone an inclusive and non‑discriminating working environment.

Your skills and attributes for success

Essential

• PhD (or near completion) in Machine Learning, AI, Statistics, Applied Mathematics, or a related field.
• Research experience in at least one of: probabilistic machine learning, diffusion/flow‑based models.
• Proficiency in modern ML toolchains (e.g., PyTorch, JAX) and reproducible research practices.
• A track record of high‑quality publications, e.g. at ICML, NeurIPS, ICLR, AISTATS, ACL, EMNLP, CVPR, JMLR, Machine Learning, and computational statistics journals.
• Excellent communication skills and a collaborative mindset.

Desirable

• Research experience in mutual information estimation and/or experimental design.
• Research experience in energy‑based models and/or hierarchical generative models.
• Strong cross‑disciplinary experience and expertise.
• Strong software engineering practices (testing, benchmarking, packaging, CI).

This post is full‑time (35 hours per week); however, we are open to considering flexible working patterns. We are also open to considering requests for hybrid working (on a non‑contractual basis) that combines a mix of remote and regular on‑campus working.

Contact details for enquiries

For Dr Siddharth N.: [e-mail] – Siddharth – Home

For Dr Michael Gutmann: [e-mail] – Michael U. Gutmann

How to apply

Please include the following documents in your application:

• CV, including publication lists and links to relevant software packages
• A 2‑3 page research statement (a) your relevant research experience and publications, (b) your proposed research and how it connects to the topics above. The page limit includes references and figures.

If shortlisted, you will be asked to provide reference letters.

About the EPSRC Hub in Generative AI

The Hub (https://www.genai.ac.uk/) is a UK‑wide research initiative dedicated to developing the next generation of Generative AI models, bringing together research groups from UCL, Oxford, Cambridge, Manchester, and Cardiff, alongside industry partners. It seeks to transform science, industry, the economy, and society by uniting leading experts from academia and industry to collaborate on impactful, large‑scale projects that no single organisation can deliver on its own. As a member of the Hub, you will:

• Engage with a broad community of researchers and practitioners in generative AI, statistics, and machine learning.
• Access opportunities for cross‑site collaboration, research visits, and industry engagement.
• Contribute to shared Hub activities (seminars, workshops, etc).

We expect the postdoc to proactively engage and collaborate with the Hub members beyond the immediate team. Specific collaborators within the Hub will be identified jointly after appointment, aligned with your expertise, interests, and the evolving needs of the project and the Hub.

As a valued member of our team, you can expect:

• A competitive salary.
• An exciting, positive, creative, challenging and rewarding place to work.
• To be part of a diverse and vibrant international community.
• Comprehensive Staff Benefits, including generous annual leave entitlement, a defined benefits pension scheme, a wide range of staff discounts, family‑friendly initiatives, and flexible work options. Check out the full list on our staff benefits page and use our reward calculator to discover the value of your pay and benefits.

Championing equality, diversity, and inclusion

The University of Edinburgh holds a Silver Athena SWAN award in recognition of our commitment to advance gender equality in higher education. We are members of the Race Equality Charter, and we are also Stonewall Scotland Diversity Champions, actively promoting LGBT equality.

Prior to any employment commencing with the University, you will be required to evidence your right to work in the UK. Further information is available on our right to work webpages. The University may be able to sponsor the employment of international workers in this role. This will depend on a number of factors specific to the successful applicant.

Key dates to note

The closing date for applications is 17th April 2026.

Unless stated otherwise the closing time for applications is 11:59pm UK time. If you are applying outside the UK the closing time on our adverts automatically adjusts to your browsers local time zone.