Join us.


Cheminformatics Data Scientist Intern · London

The Company

BenevolentAI unites technology with human intelligence to re-engineer drug discovery and deliver life-changing medicines. We have developed the Benevolent Platform®, a drug discovery platform built on powerful data foundations with state of the art machine learning and AI technology. Our technology empowers scientists to decipher the vast and complex code underlying human biology, find new ways to treat disease and personalise medicines to patients. Benevolent has active in-house R&D drug programmes in disease areas such as neurodegeneration, immunology, oncology and inflammation and has research and commercial collaborations with leading pharmaceutical and research organisations. The company is headquartered in London with a research facility in Cambridge (UK) and a further office in New York.

Who we are

We are an eclectic bunch at Benevolent, united by our belief that innovative thinking and purposeful technology can truly change outcomes for the better. Our mission is to re-engineer drug discovery and deliver life-changing medicines for patients in need and we do this by applying AI, machine learning and other advanced technologies to reinvent the ways drugs are discovered and developed. We strive to bring together unique skills and perspectives across biology, chemistry, engineering, AI research, informatics, precision medicine and drug discovery.

The Role

As a Cheminformatics Data Scientist Intern you will explore the latest updates regarding uncertainty in Quantitative Structure-Activity Relationship models and apply these to BenevolentAI models. You will ensure that the chosen uncertainty methods are appropriate and effective on a wide variety of model architectures and explore questions such as: How does uncertainty interact with applicability domains? And can a combination of uncertainty and applicability domains be used to identify accurate prospective predictions?

Primary Responsibilities

  • Build predictive models and apply innovative ideas and best practices in their generation and application to drug discovery projects.
  • Explore and apply the latest methodology in quantifying model uncertainty
  • Collaborate and communicate effectively with members of the Chemoinformatics, Bioinformatics, Drug Discovery, Artificial Intelligence, Data Science, Engineering, UX and Product teams.

We are looking for someone with

  • Someone with a PhD (or currently working towards completion of a PhD) in the field of Chemoinformatics, Computational Chemistry, Molecular Modelling, Machine Learning applied to Chemistry, or a closely related field.
  • Competent in Python.
  • Good understanding of machine learning and artificial intelligence.
  • Excellent communicator, especially when working with colleagues from other specialities.
  • Familiarity with chemical descriptors and property predictors.
  • Bonus points for experience in drug development.
  • Familiarity with popular machine learning libraries would be advantageous e.g. scikit-learn, PyTorch, TensorFlow.


Applications close on February 12th, 2021. In addition to your CV, please send us a cover letter.

Terms and Conditions

Salary: We offer remuneration for the duration of the internships. However, remuneration remains subject to the University regulations & T&C’s - should they not comply with our policy, we reserve the right to review the salary allowance.

Together, we envision a world in which no disease goes untreated. If you are benevolent, curious, want to tackle real world problems and are willing to embrace new ideas, hit that ‘apply’ button and join us.

Important Note

It has come to our attention that unfortunately fraudsters have been falsely offering jobs and set-up fake interviews under the guise of being a Benevolent recruiter. We therefore advise you to be very stringent about who is reaching out to you. Any enquiry from our team will only be made via the email or an email from this domain Please flag any suspicious contact request to