Research Associate in Topological Deep Learning for AI4Science

Job number **ENG03840** Faculties **Faculty of Engineering** Departments **Department of Computing** Salary or Salary range **£43,863\- £57,472 per annum** Location/campus **South Kensington Campus \- Hybrid** Contract type work pattern **Full time \- Fixed term** Posting End Date **30 Mar 2026** Join the CIRCLE group, in a postdoc research role to lead transformative projects spanning theoretical research and practical applications. **About the role** ------------------ Are you a researcher eager to push the boundaries of topological and geometric machine learning? Join the CIRCLE group at Imperial College London, led by **Dr. Tolga Birdal**, in a fully funded postdoctoral research role to lead transformative projects spanning theoretical research and practical applications. **Overview****.** The CIRCLE group at Imperial is seeking highly motivated and talented Postdoctoral Research Associates, who have demonstrated competence in conducting cutting\-edge research. The positions are fully funded in the context of Prof. Birdal’s UKRI Future Leaders Fellowship, and focus on the design, development, and application of **topological and geometric machine learning techniques**, with a view to **solving complex AI4Science problems** in areas ranging from 3D generative models of proteins and molecules to physics and material simulations. **What you would be doing** --------------------------- Successful candidates will be involved in projects exploring novel ways to incorporate topological structures into deep learning pipelines, contributing to both theoretical advancements and practical applications. To this end, the project integrates state\-of\-the\-art knowledge from different disciplines such as algebraic topology, differential geometry, machine learning, and computer vision. You will conduct original research in the new and exciting field of topological deep learning and explore its applications across diverse domains. You will develop novel algorithms that leverage topological and geometric techniques. In doing so, you will collaborate with a team of expert researchers in computer vision, machine learning, mathematics, and related fields. We strive in publishing in top\-tier conferences and journals. **What we are looking for** --------------------------- * Self\-driven and motivated individuals with genuine love for this field of research. * Strong track record in top conferences and journals on the field of machine learning / computer vision such as NeurIPS, CVPR, ICCV, ICML, ECCV, ICLR etc. * Excellent skills in mathematics, especially knowledge in algebraic topology and differential geometry is desirable. * Experience working with deep learning libraries such as Pytorch / JAX. * Domain knowledge in proteins / molecules and familiarity with our software, TopoX, is desirable * A PhD in computer science, mathematics or equivalent experience. Please see job description for a full list of requirements **What we can offer you** ------------------------- * The opportunity to continue your career at a world\-leading institution and be part of our mission to continue science for humanity. * Grow your career: gain access to Imperial’s sector\-leading dedicated career support for researchers as well as opportunities for promotion and progression. * Sector\-leading salary and remuneration package (including 41 days off a year and generous pension schemes). * Be part of a diverse, inclusive and collaborative work culture with various staff networks and resources to support your personal and professional wellbeing. **Further information** ----------------------- Full\-time, Fixed term contract to start as soon as possible for 12 months. * Candidates who have not yet been officially awarded their PhD will be appointed as Research Assistant within the salary range £43,863 \- £47,223 per annum. In addition to completing the online application candidates should attach: * A full CV with a list of all publications * A 2\-page research statement indicating what you see are interesting research issues relating to the above post and why your expertise is relevant. Informal enquiries related to the position should be directed to Dr Tolga Birdal t.birdal@imperial.ac.uk For queries regarding the application process contact Jamie Perrins: j.perrins@imperial.ac.uk **Available documents** ----------------------- Attached documents are available under links. Clicking a document link will initialize its download. Please note that job descriptions are not exhaustive, and you may be asked to take on additional duties that align with the key responsibilities mentioned above. We reserve the right to close the advert prior to the closing date stated should we receive a high volume of applications. It is therefore advisable that you submit your application as early as possible to avoid disappointment. If you encounter any technical issues while applying online, please don't hesitate to email us at support.jobs@imperial.ac.uk. We're here to help. ### **About Imperial** Welcome to Imperial, a global top ten university where scientific imagination leads to world\-changing impact. Join us and be part of something bigger. From global health to climate change, AI to business leadership, here at Imperial we navigate some of the world’s toughest challenges. Whatever your role, your contribution will have a lasting impact. As a member of our vibrant community of 22,000 students and 8,000 staff, you’ll collaborate with passionate minds across nine London campuses and a global network. This is your chance to help shape the future. We hope you’ll join us at Imperial College London. ### **Our Culture** We work towards equality of opportunity, to eliminating discrimination, and to creating an inclusive working environment for all. We encourage applications from all backgrounds, communities and industries, and are committed to employing a team that has diverse skills, experiences and abilities. You can read more about our commitment on our webpages. Our values are at the root of everything we do and everyone in our community is expected to demonstrate respect, collaboration, excellence, integrity, and innovation.