We are looking for a highly experienced Cheminformatician or Computational Chemist, with an extensive background in small molecule drug discovery, to lead our Cheminformatics and Computational Chemistry team.

The Cheminformatics 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. Their 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 Director of Cheminformatics & Computational Chemistry, you will lead the team in meeting this challenge. You will coordinate, support and guide them in applying cheminformatics, data analysis, biomolecular structural analysis and computational modelling techniques to advance our small molecule drug discovery programmes. You will also take an active role in the delivery of our drug discovery programmes, by developing and applying computer-aided drug discovery strategies that maximise success. Furthermore, you will collaborate with scientific and engineering teams from across the company to guide them on the best use of chemical data, and assist in the design of chemistry-related tools and infrastructure.

• Lead a highly effective multidisciplinary team of Cheminformaticians, Computational Chemists and a Cheminformatics Software Developer
• Drive the team’s computer-aided drug design strategy, and work with Lead Medicinal Chemists to devise computationally enabled chemistry strategies for specific small molecule drug discovery projects
• Coordinate the team’s work across multiple drug discovery projects from early hit ID through to candidate selection, working closely with Project Leads to scope out work and ensure delivery
• Provide computational and modelling support to drug discovery projects, both directly and as a consultant, applying a wide range of computer-aided drug design techniques to identify and develop small molecules
• Oversee the continued development of our technical capabilities and work with engineering teams to ensure the team’s infrastructure needs are met
• Act as the primary domain expert for cheminformatics and/or computational chemistry and the handling of biochemical data, and consult with scientific and engineering teams across BenevolentAI
• Collaborate and communicate effectively with members of the Medicinal Chemistry, Biology, Bioinformatics, Artificial Intelligence, Engineering and Product teams
• Champion the team’s computer-aided drug discovery capabilities and present them at meetings, conferences and to potential collaborators and investors
• Define and monitor team and individual goals, in line with company and department objectives, and conduct performance reviews for direct reports and oversee those conducted by line-managers within the team
• Nurture talent at BenevolentAI by sharing experience and offering a mentoring role

Essential Skills:

• PhD or equivalent in Chemoinformatics, Computational Chemistry, Molecular Modelling or a closely related field.
• 10+ years of experience applying cheminformatics and/or computational chemistry techniques to small molecule drug discovery in pharma, biotech or academic drug discovery unit
• Extensive practical experience of computer-aided drug design, such as compound library design, similarity and substructure searching, docking, virtual screening, reaction enumeration, molecular fragmentation, structure-based drug design, pharmacophore modelling, molecular dynamics simulations, R-group analysis and combinatorics, multi-parameter optimisation etc.
• Strong experience leading and line-managing a diverse team of scientific and technical experts to ensure delivery of goals, including mentoring junior team members and experience with conflict resolution
• Strong and demonstrable knowledge of machine learning and QSAR modelling techniques applied to chemical and biological data, 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
• Experience with a range of cheminformatics and computational chemistry software such as Schrodinger DD suite, MOE, KNIME, Pipeline Pilot, ChemAxon tools etc.
• Strong and demonstrable programming and technical skills, and an understanding of software development best practices (e.g. unit testing, continuous integration etc.)
• Excellent communication and presentation skills, especially when working with colleagues from other specialities, and extensive experience with public speaking
• 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

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 open source and proprietary chemoinformatics and computational chemistry toolkits, e.g. RDKit or other leading industry toolkits
• Familiarity with modern software development paradigms, including containerisation with Docker, GitOps, and cloud computing on AWS with Kubernetes

BenevolentAI (AMS: BAI) is a leading, clinical-stage AI-enabled drug discovery and development company listed on the Euronext Amsterdam stock exchange. Through the combined capabilities of this AI platform, its scientific expertise, and wet-lab facilities, BenevolentAI is well-positioned to deliver novel drug candidates with a higher probability of clinical success than those developed using traditional methods. The Benevolent Platform™ powers the Company’s in-house drug pipeline and supports successful collaborations with AstraZeneca, as well as leading research and charitable institutions.