Research Associate in AI for Chemistry

Job description

About the role

We are seeking a Research Associate to join our team as part of the AI for Chemistry (AIchemy) hub, specialising in multi-modal generative AI for small molecules conditioned on experimental spectra.

AIchemy, funded by the EPSRC, is a research hub dedicated to advancing artificial intelligence (AI) and machine learning (ML) in the field of chemistry. AIchemy aims to develop new AI approaches and promote their adoption within the chemistry community. The hub unites AI researchers from various subdisciplines, including computer science and both experimental and computational chemists, fostering connectivity, training, networking, and state-of-the-art research.

This position offers an exciting opportunity to design and implement novel algorithms in generative AI applicable across large-scale multi-modal chemistry data (including experimental properties) while collaborating with the larger team at Imperial College London and across the UK-wide AIchemy Hub to collectively advance AI in chemistry.

The Research Associate will co-develop the project in partnership with experimental and theoretical chemists, and machine-learning academics across the Chemistry and Computing Departments. This position provides academic freedom and will leverage the deep scientific base of the broader AIchemy Hub, including self-driving labs and high-throughput synthesis and analysis setups, enabling you to make a significant contribution to the field. You will join a cohort of computational and experimental researchers, technicians, and software engineers working at the AI/Chemistry interface and a thriving community of events and initiatives that you can take a role in shaping.

What you would be doing

• Implement and develop methods for the computational generation of small molecules and materials, which have the potential to be synthesised by experimental collaborators.
• Explore how multi-modal chemistry data (molecular and crystal structures, experimental spectra, computed and measured properties) can be incorporated into the generation process.
• Collaborate and cooperate with partners of AIchemy and other AI for Science projects funded by the UK EPSRC.
• Act as the representative for Imperial College London in meetings, conference calls and present research at conferences, workshops, and open days, and publish research results in journals.
• Assist in the supervision of undergraduate and postgraduate research students and research assistants as required, designing projects and helping make decisions about research directions.
• Take the initiative in the planning of research, co-developing your project with a range of academic mentors.
• Develop and maintain open-source software together with other group members.

What we are looking for

• Practical experience of developing and applying generative model architectures, such as diffusion, flow-matching or autoregressive models, to molecules or materials.
• Knowledge of machine learning representations for molecules and materials, such as graph neural networks and equivariant networks.
• Machine learning algorithms and model development experience.
• Successful experience of working with multidisciplinary experimental and theory collaborators.
• Practical experience within a research environment and publications in relevant peer-reviewed journals.

What we can offer you

• The chance to join the AIchemy Hub , a multidisciplinary team working at the forefront of AI in Chemistry.
• 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.
• As a member of research staff you have 10 development days to use to develop your skills and explore your career prospects
• Sector-leading salary and remuneration package (including 43 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

Please note that this is a PhD level role but candidates who have not yet been officially awarded will be appointed as a Research Assistant.

This is a full-time post (35 hours per week).

This role is for a fixed-term contract for 12 months.

If you require any further details about the role, please contact: Alex Ganose - [email protected]