Skip to content

Twitter
Facebook
LinkedIn Page
Linkedin Group
Instagram
Meetup
Github

WiMLDS

Women in Machine Learning & Data Science

Chapters
North America: USA
Atlanta – USA
Austin – USA
Baltimore – USA
Bay Area – USA
Boston – USA
Boulder – USA
Charlottesville – USA
Chicago – USA
Columbus – USA
Corpus Christi – USA
Dallas Fort Worth – USA
Denver – USA
Detroit Metro – USA
Kansas City – USA
Los Angeles – USA
Milwaukee – USA
Minneapolis – USA
North Carolina – USA
NYC – USA
Omaha – USA
Pittsburgh – USA
Salt Lake City – USA
San Antonio – USA
Seattle – USA
Syracuse – USA
Vermont – USA
Washington, DC – USA
North America: Canada
Calgary – Canada
Edmonton – Canada
Halifax – Canada
Montreal – Canada
Ottawa – Canada
Toronto – Canada
Vancouver – Canada
Africa
Abuja – Nigeria
Accra – Ghana
Algiers – Algeria
Gaborone – Botswana
Casablanca – Morocco
Dakar – Senegal
Khartoum – Sudan
Kinshasa – DRC
Lagos – Nigeria
Nairobi – Kenya
Kampala – Uganda
Vacoas-Phoenix – Mauritius
Yaoundé – Cameroon
Asia
Amaravathi – India
Bengaluru – India
Bhopal – India
Chennai – India
Delhi – India
Goa – India
Hyderabad – India
Indore – India
Jaipur – India
Manila – Philippines
Mumbai – India
Mysore – India
Pune-India
Singapore – Singapore
Surabaya – Indonesia
Tokyo – Japan
Ulaanbaatar – Mongolia
Visakhapatnam – India
Middle East
Ankara – Turkey
Cairo – Egypt
Istanbul – Turkey
Riyadh – Saudi Arabia
Tel Aviv – Israel
Europe
Amsterdam – Netherlands
Berlin – Germany
Brussels – Belgium
Bucharest – Romania
Copenhagen – Denmark
Cambridge – United Kingdom
Dresden – Germany
Dublin – Ireland
Galicia – Spain
Limassol – Cyprus
London – United Kingdom
Madrid – Spain
Milan – Italy
Munich – Germany
Paris – France
Poznan – Poland
Sophia – Antipolis-France
Trojmiasto – Poland
Zurich – Switzerland
South America
Buenos Aires – Argentina
Cochabamba – Bolivia
La Paz – Bolivia
Rio de Janeiro – Brazil
São Paulo – Brazil
Oceania
Melbourne – Australia
Sydney – Australia
Press
Blog
Contact
Events
Open Source Sprints
Berlin Scikit Sprint 2020
Nairobi Scikit Sprint 2019
NYC Scikit Sprint 2019
Bay Area Scikit Sprint 2019
NYC Scikit Sprint 2018
NYC Scikit Sprint 2017
Hackathons
Smart Cities
Healthcare
Jobs
Job Listings
Post a Job
More
Leadership
Code of Conduct
Become a Sponsor
Donate





Research Fellow in Few step Generative Modelling

Research Fellow in Few step Generative Modelling

Full Time
Hybrid between University of Cambridge Department of Engineering / remote / visits to UCL
Posted 2 months ago

Website University College London

About Us

UCL’s Department of Computer Science (CS) is a top-ranked Computer Science Department in the UK. In the 2021 Research Excellence Framework (REF) evaluation, UCL Computer Science was ranked second in the UK for research power and first in England.

This fellowship is funded by the UKRI (EPSRC) AI Hub in Generative Models (grant number EP/Y029763/1). This hub is a UK-wide research initiative dedicated to developing the next generation of Generative AI models. 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. There is an expectation to proactively engage and collaborate with other Hub members and partner institutions, engaging with central Hub activities, cross-theme initiatives, and events.

Successful applicants will investigate few-step generative models, including diffusion, consistency, flow-based, and related probabilistic methods, with the aim of developing computationally efficient and theoretically grounded approaches that maintain high-quality generation performance while reducing sampling cost. The work will involve developing stable training and inference methods, conducting probabilistic modelling research, and performing large-scale computational experiments using standard machine learning frameworks and publicly available scientific datasets.

This post will be funded until 31st October 2028 in the first instance.

Appointment at Grade 7 is dependent upon having been awarded a PhD; if this is not the case, initial appointment will be at Grade 6B (salary £39,148 – £41,833per annum) with payment at Grade 7 being backdated to the date of final submission of the PhD Thesis.

About The Role

This unique position is part of a strategic collaboration between University College London (UCL) and the University of Cambridge under the AI Hub in Generative Models. The successful candidate will benefit from the world-class facilities and expertise at both institutions,



working under the joint supervision of Professor José Miguel Hernandez Lobato and Professor David Barber. The position is hosted by the University of Cambridge and may require academic visits to the UCL Centre for Artificial Intelligence to support a co-supervision model.

Key duties and responsibilities include working on deep learning, probabilistic modelling, transformer-based models, diffusion models, flow matching or consistency models, publishing papers and co-supervising PhD and master students.

About You

Successful applicants will have, or be near to completing, a PhD in computer science, information engineering, statistics or a related area, with extensive research experience and a strong publication record. Excellent mathematical and programming skills are essential, with experience in two or more of Bayesian methods, deep learning, diffusion models, flow matching or transformer-based models.

A job description and person specification can be accessed at the bottom of this page. To apply for the vacancy please click on the ‘Apply Now’ button below.

If you have any queries regarding the vacancy or the application process, please contact the AI Hub in Generative Models [email protected].

What We Offer

As well as the exciting opportunities this role presents, we also offer outstanding benefits. Please visit https://www.ucl.ac.uk/work-at-ucl/rewards-and-benefits to find out more.

Our commitment to Equality, Diversity and Inclusion

As London’s Global University, we know diversity fosters creativity and innovation, and we want our community to represent the diversity of the world’s talent.

We are committed to equality of opportunity, to being fair and inclusive, and to being a place where we all belong. We therefore particularly encourage applications from candidates who are likely to be underrepresented in UCL’s workforce.

These include people from Black, Asian and ethnic minority backgrounds; disabled people; LGBTQI+ people; and for our Grade 9 and 10 roles, women. Our department holds an Athena SWAN Bronze award, in recognition of our long-term commitment and ‘beacon’ status in advancing gender equality.

We are in the process of applying for an Institute of Physics Inclusion Award. You can read more about our commitment to Equality, Diversity and Inclusion here:https://www.ucl.ac.uk/equality-diversity-inclusion/

To apply for this job please visit www.ucl.ac.uk.

Post navigation

Postdoctoral Scholarship in Geometric Deep Learning / Scientific Machine Learning

AI Studio Coach

Copyright © 2026 WiMLDS Theme: Flash by ThemeGrill. Proudly powered by WordPress
#J-18808-Ljbffr

📌 Research Fellow in Few step Generative Modelling (Ontario)
🏢 Women In Machine Learning And Data Science, Mumbai
📍 Ontario