We invite applications to this project for a fully funded four-year EN & MN Lindsay Endowed PhD studentship. The student will be based in the School of Life Sciences, one of the UK’s flagship institutions for biological research.
Molecular recognition, the specific interaction between two or more molecules through noncovalent bonding, plays an important role in biological systems and is fundamental for the development of small molecules capable of modulating biochemical processes to treat diseases.
Computer-aided drug discovery approaches are a fundamental component of the drug discovery process allowing the study of the molecular recognition event at an atomic level and supporting rational molecular design. In the last decade there has been a significant expansion of insilico approaches in Computational Chemistry and today, alongside the traditional molecular modelling techniques, machine learning and artificial intelligence methods are starting to have an impact on the drug discovery process. Development in molecular dynamics methods also offer a deeper understanding of how designed compounds interact with their biological target.
Proposal. To explore the use of advanced CADD methodologies for the identification and optimisation of bioactive compounds in the context of the ongoing drug discovery projects at the Drug Discovery Unit.
The student will have the opportunity to apply advanced computational chemistry approaches to address different scientific questions in projects at different stages of the development process (from hit identification to hit-to-lead and lead optimisation). The student will also contribute to the improvement and development of the in-house Insilico drug discovery platform focused on integrating quantum mechanics, machine learning and AI approaches to drive compounds multiparameter optimisation and virtual screening of ultra-large chemical space
The student will be embedded in the Computational Chemistry team of the Drug Discovery Unit and will work in highly multidisciplinary research teams (comprising of medicinal chemists, structural biologists, biologists, ADME/PK experts) focused on identification and optimisation of active compounds for neglected and tropical diseases. The student will also have access to:
· industry gold standard computational chemistry software
· high performing computing capabilities
· in house tools for machine learning and AI driven drug discovery
· in house insilico drug discovery platform
Applicants are expected to hold (or be about to achieve) at least a 2:1 Honours degree in a relevant subject or demonstrably equivalent experience. Previous experience in Computational Chemistry, Machine Learning and programming in Python would be favourable.
This studentship is funded by the EN & MN Lindsay Scholarship. The 4-year studentship comes with a stipend of £16k per annum plus generous research funds of £5,000 per annum.
Applications are open to candidates classed as Home and Rest of UK (RUK) / Channel Islands or Isle of Man students. This includes UK, EU and Irish Nationals who meet the residency requirements of the University, please see here for more information. Please check the requirements carefully to ensure you qualify.
Please note the deadline for applications is Friday 22nd July 2022.