UCL Research Fellow: Generative Models

Join UCL’s research team as a Research Fellow focusing on few-step generative models. This full-time, hybrid position involves deep learning and probabilistic methods to advance generative model performance.

The fellowship offers a unique opportunity to engage in cutting-edge research funded by the UKRI AI Hub, running through October 2028. You will work on methodological advancements in diffusion models and flow matching while also performing large-scale computational experiments. Importantly, you will help co-supervise students and disseminate findings through publications in high-impact journals.

Key Responsibilities:

• Investigate deep learning and probabilistic modelling approaches

• Implement large-scale computational experiments

• Publish high-quality research papers

• Provide mentorship to PhD and master students

• Establish robust training and inference methodologies

Requirements:

• PhD in computer science, statistics, or a relevant discipline

• Strong background in research with significant publications

• Expertise in Bayesian methods and deep learning

• Excellent programming and mathematical capabilities

• Familiarity with flow matching or transformer models

Advance your academic career with UCL and contribute to groundbreaking work in generative modelling.
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