We are looking for an experienced Principal Computational Chemist, with a keen interest in small molecule drug design, to join our Cheminformatics amp; Computational Chemistry team.
The Cheminformatics amp; 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 Computational Chemist within the team, you will apply your computational chemistry, biomolecular structural analysis and computational modelling skills to advance our small molecule drug discovery programmes. You will work closely with cheminformaticians and medicinal chemists to develop data and modelling pipelines, identify and apply innovative technologies, and employ state of the art computer-aided drug design techniques.
Responsibilities:
- Lead the computational chemistry support for one or more drug discovery projects, working closely with cheminformaticians and medicinal chemists, and the rest of the project 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 DD projects
- Collaborate and communicate effectively with members of the Chemoinformatics, Computational Chemistry, Bioinformatics, Drug Discovery, Artificial Intelligence, Engineering and Product teams
- Contribute to the development of our computational chemistry capabilities and help define the long-term strategic thinking of the computational team
- Nurture talent at BenevolentAI by sharing experience and offering a mentoring and/or line-management role, where appropriate
We are looking for:
Essential Skills:
- PhD or equivalent in computational chemistry, molecular modelling, cheminformatics or a closely related field, with experience of computer-aided drug discovery in pharma, biotech or academic drug discovery unit
- Strong and demonstrable knowledge of computational chemistry approaches and their application to small molecule drug discovery, and the ability to objectively design scientifically-merited experiments
- Practical experience of computer-aided drug design techniques, such as compound library design, virtual screening, matched-molecular pair analysis, molecular fragmentation, and/or 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
- Practical experience processing and deriving novel insights from large chemical data resources, e.g. ChEMBL, SureChEMBL, and PubChem
- Experience in a range of computational chemistry software (e.g. Schrodinger DD suite, MOE, KNIME, Pipeline Pilot).
- Innovator of new ideas and approaches in computational chemistry and cheminformatics 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
Desired Skills:
- 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