Mitigating Synthesisability Loss in 3D Generative Models

The molecule design process is often hampered by high costs and lengthy development cycles. Recent advances in 3D-aware generative models offer a promising route to accelerate novel molecule discovery, yet these approaches frequently produce compounds that are not practically synthesisable. This project will systematically investigate how 3D-molecular novelty impacts synthesisability and will develop methods to mitigate this loss. Building on state-of-the-art 3D architectures, the research will quantify the synthesisability gap by integrating conditioning constraints from high-quality informatics sources such as the Cambridge Structural Database. Multiple levels of 3D complexity, e.g., the incorporation of interaction field constraints from resources like Isostar, Superstar, and hotspot potentials—will be developed to understand their impact on synthesisability. Validation will be achieved through case studies targeting well-characterised systems (e.g., hERG and neglected tropical disease targets), ensuring that the outputs have direct relevance to molecule discovery pipelines. The project is positioned to bridge the gap between digital design innovation and practical synthesis, addressing a critical bottleneck in AI-driven materials chemistry.

This project will be supervised by Dr Anthony Bradley (Department of Chemistry), Dr Gabriella Pizzuto (Department of Computer Science and Informatics), Dr John Ward (Department of Chemistry), Dr Ian Wall (GlaxoSmithKline) and Dr Bojana Popovic (Cambridge Crystallographic Data Centre).

The team is world-leading in this topic and provides a cross- and inter-disciplinary environment across Chemistry Automation, Drug Discovery, AI, and Robotics. Anthony Bradley, is an ECA on a joint appointment between Chemistry and Computer Science, and his research is in experimental and computational automation in molecule development. He co-developed the first 3D-aware generative deep models and has designed molecules in clinical studies. Gabriella Pizzuto is an ECA on a joint appointment between Computer Science and Chemistry, holds a RAEng Research Fellowship, is Co-I and ECR committee co-chair on AIchemy and RAL at the Royce Institute. Her research at the intersection of robot learning and control have been outstanding paper finalists at flagship robotics conferences. Ian Wall, as Head of Computer Aided Molecule Design at GSK, offers decades of expertise in designing molecules using computation. Bojana Popovic contributes deep knowledge in 3D molecule design and function as Discovery Sciences Lead at CCDC. Together, their collective strengths and proven track records in both methodological innovation and practical application provide an ideal mentoring environment.

This project is expected to start in October 2026 and is offered under the EPSRC Centre for Doctoral Training in Digital and Automated Materials Chemistry based in the Materials Innovation Factory at the University of Liverpool, the largest industry-academia colocation in UK physical science. The successful candidate will benefit from training in robotic, digital, chemical and physical thinking, which they will apply in their domain-specific research in materials design, discovery and processing. PhD training has been developed with 35 industrial partners and is designed to generate flexible, employable, enterprising researchers who can communicate across domains.

We strongly encourage candidates to get in touch with the supervisory team to get a better idea of the project before making a formal application online. Any informal enquiries about the project can be directed to Anthony.Bradley@liverpool.ac.uk.

Review our CDT guide on "How to Apply" carefully as it may differ from a standard application process. You may need the following documents to complete your online application:

• University transcripts and degree certificates to date
• Passport details
• English language certificates (international applicants only)
• A personal statement
• A curriculum vitae (CV)
• Contact details for two proposed supervisors
• Names and contact details of two referees.

Finally, register and apply online. You'll receive an email acknowledgment once you've submitted your application. We'll be in touch with further details about what happens next.

Please ensure you include the project title and reference number CCPR180 when applying indicating the subject area as Chemistry. We will interview on a rolling basis and fill the position on a first come, first served principle. We will close the application once a suitable candidate is found (this may be before the deadline) hence early application is advised.

We want all our Staff and Students to feel that Liverpool is an inclusive and welcoming environment that actively celebrates and encourages diversity. We are committed to working with students to make all reasonable project adaptations including supporting those with caring responsibilities, disabilities or other personal circumstances.

The EPSRC DAMC CDT Studentship will cover full home tuition fees and a maintenance grant for 4 years starting at the UKRI minimum (£21,805 for 2026-27 academic year). The Studentship also comes with a Research Training Support Grant to fund consumables, conference attendance, etc.

Studentships are available to any prospective student wishing to apply including both home and international students. While EPSRC funding will not cover international fees, a limited number of scholarships to meet the fee difference will be available to support outstanding international students.

If you have a disability you may be entitled to a Disabled Students’ Allowance on top of your studentship to help cover the costs of any additional support that a person studying for a doctorate might need as a result.