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Queen Mary University of London

UKRI/BBSRC Artificial Intelligence for Drug Discovery Doctoral Training Programme (UKRI-AIDD)


Discovery of new pharmaceutical drugs is a key front in the battle against the adverse effects of ageing towards healthier longer lives. In recent years artificial intelligence (AI) has revolutionised the drug discovery process, promising the development of safer, more effective treatments in shorter timescales. This has generated high demand for researchers capable of developing AI approaches to answer complex biological questions.

UKRI-AIDD is an innovative doctoral training programme delivered by leading drug discovery companies (Exscientia, Heptares and MSD) in collaboration with Queen Mary University of London (QMUL). Together, with support from UKRI-BBSRC, we aim to train a next generation of interdisciplinary researchers working closely with industry at the intersection of artificial intelligence and bioscience.

Projects available

This year we are offering up to eight fully funded four-year PhD project opportunities, covering biological applications of text mining, machine learning, network science, knowledge graphs, multi-omics, data integration, computational chemistry, computer vision, bioinformatics and molecular modelling. For project details and supervisory teams, please visit website.

Unique benefits of joining this PhD programme include an enhanced stipend, increased training opportunities, including a bespoke training pathway, designed for, and in conjunction with each student. The opportunity to engage with industry partners, including the option for students to spent three months of their studies on a placement within a company, and extensive networking opportunities and access to our high-performance computing facilities.

Eligibility and applying

We are looking for highly motivated individuals who are passionate about contributing to new discoveries in drug discovery bioscience through the application of the latest techniques in AI and data science. Ideal candidates will have a grounding in both a natural science and data science, e.g. through a Master's degree in a subject such as bioinformatics or computational chemistry. Alternatively, you may have, for example, a first-class degree in computer science followed by biochemistry experience, or vice versa (qualifications and evidence thereof must be obtained before 19/09/2023). You will be confident in performing data wrangling and analysis in a language such as Python, R or C++. Effective communication skills are essential.

The deadline for applications is January 22nd 2023 and projects start in September 2023.
For more details, including eligibility and how to apply, see website.

Shortlisted applicants will be invited for a formal interview by UKRI-AIDD supervisors.

Artificial Intelligence for Drug Discovery Collaborative Training Programme (AIDD-CTP)

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