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Designing new molecules against Alzheimer’s disease using artificial intelligence techniques


   Information School

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  Dr A de la Vega de Leon, Prof B Chen  No more applications being accepted  Funded PhD Project (European/UK Students Only)

About the Project

The Sheffield Chemoinformatics Research Group is pleased to offer a fully-funded 3.5 year PhD studentship. The student will be based at the University of Sheffield’s Information School (ranked best in UK and Europe in its field by the QS University ranking 2019) and will collaborate closely with Professor Beining Chen’s Medicinal Chemistry group in the Department of Chemistry.

Project description
Alzheimer’s disease (AD) is the most common type of dementia in the UK. According to the Alzheimer’s society, the number of people with dementia in the UK is expected to reach 1 million by 2025. There is currently no cure for AD and clinical trials of drug candidates have been unsuccessful, so there is still a large unmet need for a treatment against AD.

Artificial intelligence techniques, such as generative models, have become very popular in pharmaceutical research. Generative models are machine learning tools that can design novel molecules. These techniques hold great promise as an alternative to traditional techniques, where molecules are built up from small fragments. Recent research has shown that generative models can be trained to produce molecules active against a specific protein. The main aim of the PhD is to explore the possibility of training models that generate molecules active against more than one protein. Molecules with activities against several proteins are ideal drug candidates for complex diseases such as AD, where different cellular pathways are affected.

In this PhD, the successful applicant will focus on investigating how the knowledge of different biological activities is learnt and transferred when training generative models. They will test different strategies to explore under what conditions are generated molecules are active against desired proteins, with a focus on proteins known to be involved in the progression of AD.


Joint supervisors
Dr Antonio de la Vega de León, Lecturer in Chemoinformatics
Professor Beining Chen, Professor in Medicinal Chemistry


Requirements
This PhD is available to UK and EU candidates in possession (or expected to possess before the beginning of the PhD) of a 2(i) (or equivalent) degree in Computer Science, Chemistry or Biology. For EU candidates, an overall IELTS score of 6.5 with at least 6.0 in each component is required. Candidates of computer science students with an interest in biomedical research, as well as chemistry and biology with an interest in computer science and machine learning are strongly encouraged to apply. More details regarding the formal PGR requirements can be found at the following link: https://www.sheffield.ac.uk/is/pgr/apply

Funding
UK/EU applicants will be eligible for a full award paying fees and maintenance at standard Research Council rates. The UKRI stipend rate for 2020/21 is £15,285 per annum. Funding also includes a RTSG of £4,500 for the whole PhD.

Application process
Prospective applicants should send their CV and two reference letters to [Email Address Removed] or [Email Address Removed]. Pre-selected candidates will be invited to interview.
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