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Technology
London

Senior Cheminformatics Data Scientist - AI/ML Specialist

With over 35 nationalities and a range of backgrounds represented in our Benevolent team, we aim to build an inclusive environment where our people can bring their authentic selves to work, be respected for who they are and the exceptional work they do. We welcome and actively encourage applications from all sections of society and are committed to offering equal employment opportunities regardless of sex, race, religion or belief, ethnic or national origin, marital, domestic or civil partnership status, sexual orientation, gender identity, parental status, disability, age, citizenship, or any other basis. We see our diversity as an asset as we tackle challenging problems that bridge the gap between drug discovery and technology.

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The Role

We are looking for an experienced Senior Cheminformatics Data Scientist, specialising in AI/ML, with a demonstrable expertise in QSAR modelling and the development of AI/ML methods for chemistry. This role represents an opportunity to lead our QSAR modelling initiatives within cheminformatics, and to positively impact the advancement of our small molecule Drug Discovery programmes.

You will contribute to 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.

We’ve assembled an exceptionally diverse, talented and spirited team who sincerely enjoy coming to work every single day to bring their ideas and a real passion for new technology and medical discovery. You will work alongside recognised thought leaders at the cross-section of Machine Learning, Chemistry data and Drug Discovery.

You will apply your skills and experience to advance the drug discovery programmes in our portfolio. This includes developing QSAR models and designing new AI/ML approaches for project-specific challenges, and applying a range of new and existing technologies to support the needs of our wider portfolio.


Primary Responsibilities

  • Lead our QSAR modelling initiatives, and find new AI/ML-driven solutions to apply to our drug discovery projects.
  • 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.
  • Collaborate and communicate effectively with members of the Chemoinformatics, Computational Chemistry, Bioinformatics, Drug Discovery, Artificial Intelligence, Engineering and Product teams.
  • Nurture talent at BenevolentAI by sharing experience and offering a mentoring role, where appropriate

We are looking for someone with

  • PhD in a field related to Chemoinformatics or Machine Learning.
  • Demonstrable experience in developing QSAR models for drug discovery, particularly in medicinal chemistry.
  • Innovator of new ideas and approaches in the field of AI for chemistry, as demonstrated by appropriate papers, presentations, and code contributions to open source projects.
  • Strong knowledge of Python, a deep learning framework (e.g. TensorFlow, PyTorch), and state-of-the art ML approaches.
  • Strong and demonstrable programming and technical skills, and familiar with open source and proprietary Chemoinformatics libraries e.g. RDKit or other leading industry toolkits.
  • Capable of processing and deriving novel insights from large chemical data resources, e.g. ChEMBL, SureChEMBL, and PubChem.
  • A solid understanding of Chemoinformatics approaches and their application to live drug discovery projects, and being able to objectively design scientifically-merited experiments.
  • Excellent communication skills, especially when working with colleagues from other specialities.
  • Experience in commercial Cheminformatics and computational chemistry tools, such as those from Schrodinger, ChemAxon, and KNIME.
  • Familiarity with modern software development paradigms, including containerisation with Docker, GitOps, and cloud computing on AWS with Kubernetes.
  • Knowledge of the drug discovery process, and an understanding of what is involved in medicinal chemistry optimisations.
  • Prior experience of drug discovery project support, such as compound library design, docking, virtual screening, molecular fragmentation, structure-based drug design, pharmacophore generation and analysis, multi-parameter optimisation.


We share a passion for being part of a mission that matters, and we are always looking for curious and collaborative people who share our values and want to be part of our journey.  If that sounds like a fit for you, hit the apply button and join us.

About us

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 its AI platform, 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 a growing in-house pipeline of 13 named drug programmes and over 10 exploratory programmes, and it maintains successful collaborations with AstraZeneca, as well as leading research and charitable institutions. BenevolentAI is headquartered in London, with a research facility in Cambridge (UK) and a further office in New York.

Want to do a little more research before you apply?

Head over to our Glassdoor page to learn about our benefits, culture and to find out what our team thinks about life at Benevolent. You can also find out more about us on LinkedIn and Twitter.

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