We are looking for a highly experienced Senior Principal Computational Chemist, with a keen interest in small molecule drug design, to join our Cheminformatics & Computational Chemistry team.
The Cheminformatics & Computational Chemistry team is a high performing cross-functional team that seeks to apply their knowledge to a diverse range of programmes from Target Identification through Hit ID, Hit Expansion and Lead Optimisation. Our role is to aid the advancement of our small molecule Drug Discovery programmes by devising computational solutions to project-specific challenges and applying new and existing technologies to support the needs of our wider portfolio.
As a Senior Principal Computational Chemist within the team you will have a significant leadership role within the team. You will utilise your extensive experience in computational chemistry, biomolecular structural analysis and computational modelling techniques to advance our small molecule drug discovery programmes. You will work closely with cheminformaticians and medicinal chemists and lead the delivery of data and modelling pipelines, identify and apply innovative technologies, and employ state of the art computer-aided drug design techniques.
- Lead the computational chemistry support for multiple drug discovery projects, working closely with cheminformaticians and medicinal chemists, and the rest of the project team
- Work with the team to identify and develop innovative approaches to expand our computational chemistry capabilities, and drive the long-term strategic thinking of the team
- Apply a wide range of computer-aided drug design techniques to identify and develop small molecules, including virtual screening, bioisosteric replacements, MMPA and de novo design
- Gather, analyse and report on biomolecular structural data to derive novel insights into SAR and protein-ligand interactions, including the use of 3D ligand- and structure-based computational and physics-based modelling
- Build, evaluate and deliver structure- and ligand-based models, e.g. pharmacophore, docking etc. to advance our small molecule DD projects, and to support their use by project teams
- Develop processes, customisable workflows and computational techniques that can be adapted and applied across the drug discovery portfolio
- Act as the key domain expert for computational chemistry and the handling of biomolecular data, and consult with scientific and engineering teams across BenevolentAI
- Collaborate and communicate effectively with members of the Chemoinformatics, Computational Chemistry, Bioinformatics, Drug Discovery, Artificial Intelligence, Engineering and Product teams
- Line-manage a portion of the team, defining and monitoring their individual goals, in line with company and department objectives, and conduct performance reviews
- Nurture talent at BenevolentAI by supporting junior members of the team in their working, sharing your experience and providing a mentoring role
We are looking for:
- PhD or equivalent in Chemoinformatics, Computational Chemistry, Molecular Modelling or a closely related field and extensive experience of computer-aided drug discovery in pharma, biotech or academic drug discovery unit
- Detailed demonstrable knowledge of a wide range of computational chemistry approaches and their application to small molecule drug discovery, and the ability to objectively design scientifically-merited experiments
- Extensive practical experience of computer-aided drug design techniques, such as compound library design, docking, virtual screening, molecular fragmentation, structure-based drug design, pharmacophore generation and analysis, multi-parameter optimisation
- Practical experience in developing, deploying and applying ligand- and structural-based modelling techniques, such as docking, pharmacophore modelling, shape similarity screening, molecular dynamics simulations, water-site analysis and/or FEP analysis, and a strong understanding of best practices
- Extensive experience processing chemical and biological data from a range of data sources, e.g. ChEMBL, SureChEMBL, and PubChem
- Experience with a range of computational chemistry software such as Schrodinger DD suite, MOE, KNIME, Pipeline Pilot, ChemAxon tools etc.
- Innovator of new ideas and approaches in the chemoinformatics and computational chemistry fields of research, as demonstrated by appropriate papers, presentations, or code contributions to open source projects.
- Excellent communication and leadership skills, especially when working with junior colleagues from a range of technical and scientific backgrounds
- Experience setting up and managing computational infrastructure for cheminformatics and computational chemistry applications
- Familiarity with machine learning and QSAR modelling techniques, and an understanding of their appropriate application and potential pitfalls
- Strong programming and technical skills, and familiarity with open source and proprietary chemoinformatics libraries, e.g. RDKit or other leading industry toolkits
- Familiarity with modern software development paradigms, including containerisation with Docker, GitOps, and cloud computing