Post Doctoral Research Associate – Chemoinformatics
Business Area: Science
Full Time Salary: £33,963 to £39,955 per annum (Discretionary range to £45,949)
Post Type: Full time / Fixed term
Term: 2 years
Provisional Interview Dates: 6th January 2020
Closing Date: 02/01/2020
Ref No: 10312
We are looking for a talented cheminformatician to join a group at the forefront of high-throughput crystallographic fragment screening for drug-discovery, with a focus on developing and implementing new algorithms to combine high-throughput natural-product discovery with rapid chemical progression of fragment compounds.
China uses around half of the antibiotics consumed worldwide. It has been previously estimated that growing antimicrobial resistance could lead to 1 million premature deaths per year in the country by 2050. These concerns – shared with the UK – are creating increasing demand for new and effective antimicrobials.
A recently funded collaborative initiative, CHNUK2, between world-leading institutions in the UK and China aims to form a hub of support platforms for fundamental and translational antibiotic discovery research. Using UK strengths in underpinning biology and science policy, the project aims to explore and exploit China’s resources in natural products and traditional Chinese medicine.
The project will complement the work of the XChem platform at Diamond (https://www.diamond.ac.uk/Instruments/Mx/Fragment-Screening.html), which offers high-throughput crystallographic fragment screening (~1000 crystals a week). The availability of targets to validate and the high-throughput X-ray experiment are currently being expanded further by a robotic synthesis platform for high-throughput synthesis, and computational tools in the cloud.
The successful candidate will act as main cheminformatician or computational chemist within the project, and will be tasked with:
- Development of new algorithms to determine available synthetic routes for elaboration or expansion of natural-products;
- Development of models (e.g. machine learning and artificial intelligence) to predict the synthetic tractability of novel derivatives of natural products;
- Implementation of existing and developed models and algorithms into our open-source cloud platform – Fragalysis (https://fragalysis.diamond.ac.uk);
- Working closely with bench-chemists to ensure optimisations in the laboratory are transferred directly into algorithms;
- Test, develop, and optimise new robotic synthesis routes (coding protocols in python).