Lead Cheminformatics Machine Learning Data Scientist
4 weeks ago
We are looking for a highly experienced Lead Cheminformatics Data Scientist, who specialises in AI/ML with a keen interest in small molecule drug design, to lead our Cheminformatics team within 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 Cheminformatics Data Scientist you will have a significant leadership role within the team. You will utilise your extensive experience in cheminformatics, data analysis and computational modelling techniques to advance our small molecule drug discovery programmes. You will work closely with medicinal and computational chemists to develop data and modelling pipelines, identify and apply innovative technologies, and employ state of the art computer-aided drug design techniques.
- Lead the cheminformatics and computational modelling support for multiple drug discovery projects and find new AI/ML- driven solutions, working closely with medicinal and computational chemists, and the rest of the project team
- Work with the team to identify and develop innovative approaches to expand our cheminformatics 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, reaction and fragment enumeration, de novo design, and chemical library design and sampling
- Gather, analyse and report on biochemical data from a range of data sources to derive novel insights into SAR and SPR, including the manipulation and analysis of biochemical data at scale
- Build, evaluate and deliver QSAR models to advance our small molecule Drug Discovery programmes, 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 cheminformatics and the handling of biochemical data, and consult with scientific and engineering teams from 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
Essential Skills:
- 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 chemoinformatics approaches and their application to live drug discovery projects, and the ability to objectively design scientifically-merited experiments
- Extensive practical experience of computer-aided drug design, such as compound library design, similarity and substructure searching, virtual screening, reaction enumeration, molecular fragmentation, R-group analysis and combinatorics, multi-parameter optimisation
- Practical experience in developing, deploying and applying machine learning and QSAR modelling techniques to chemical and biological data, and knowledge of a wide range of chemical featurisers, 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
- Strong and demonstrable programming and technical skills, and familiar with open source and proprietary chemoinformatics libraries e.g. RDKit or other leading industry toolkits
- 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
Desired Skills:
- Experience setting up and managing computational infrastructure for cheminformatics and computational chemistry applications
- Familiarity with deep learning frameworks (e.g. TensorFlow, PyTorch), and state-of-the art ML approaches.
- Familiarity with 3D ligand- and structural-based modelling techniques, such as docking, pharmacophore modelling, shape similarity screening, molecular dynamics simulations, water-site analysis and/or FEP analysis
- Familiarity with modern software development paradigms, including containerisation with Docker, GitOps, and cloud computing on AWS with Kubernetes
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