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Bioinformatics Data Scientist · London

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.


The Role

We are seeking bioinformatics data scientists to join our London teams and apply advanced bioinformatics methods and data analytics to real world drug discovery challenges. We have identified 3 projects across our Product Areas at BenevolentAI, which each give successful candidates the opportunity to learn more about leveraging biomedical data, developing targeting identification processes and establishing precision medicine workflows, all within an industry setting.

Primary Responsibilities

Project 1: Knowledge

A significant amount of the pre-clinical data accumulated by BenevolentAI from the development of biological assays to characterise drug targets and evaluate potential therapeutic molecules. Databases dedicated to manage bioassay data could provide a rich resource for drug target identification. As such, the aim of this project is to build an automatic data processing pipeline to standardise assay data ingestion into BenevolentAI’s Knowledge Graph. The opportunities offered by this project include:  

  • Learning and applying FAIR data principles (Findable, Accessible, Interoperable and Reusable)
  • Inspecting assay data content features to understand how this information can support the Drug Discovery process
  • Designing and implementing assay data models and data standardisation workflows
  • Developing data engineering skills to support the integration of assay data into the BenevolentAI’s Knowledge Graph

Project 2: Target Identification

At BenevolentAI, our teams have developed performant models by collecting and encoding biological and chemical information around biomedical entities (e.g. genes, drugs, diseases, mechanisms). We are looking for an intern to help build a catalogue of discrete latent vector representations in our feature store; a central repository of features for biomedical entities in the problems we face day-to-day. This set of representations will help facilitate rapid experimentation of new models and improve existing workflows used for target identification. Due to the nature of the work, you will be expected to liaise with various teams across the business including chemistry, target identification, and precision medicine.  You will be supported by bioinformaticians, data scientists and engineers. The opportunities offered by this project include: 

  • Using the existing data in our internal feature store to train and evaluate machine learning models
  • Developing new features based on bio/chemoinformatic and machine learning approaches
  • Supporting your team, you will implement classification models consuming biomedical data
  • Performing benchmarking, validation, and evaluation of the created models and the features they use.

Project 3: Precision Medicine

The Precision Medicine team at Benevolent is applying latent variable models (LVMs) to transcriptomics data in order to define pathologically distinct patient subgroups and their key gene regulatory mechanisms. Within the Precision Medicine Omics pipeline, the latent variables are analysed in the context of a priori defined genesets, representing known biological processes or metabolic pathways. Given the availability of high resolution single cell transcriptomics data (scRNA-seq) for many human tissues and diseases, the team is planning to use these data and identify de-novo genesets, i.e. groups of genes representing disease-specific mechanisms that would provide an enriched view of the results of our AI models in the context of drug discovery. As an intern, you will be helping the Precision Medicine team to tackle this goal. You will be supported by bioinformatics / AI data scientists and will interact with engineers and Translational Medicine Scientists. This opportunities offered by this project include: 

  • Exploring the data available at the Human Cell Atlas or analogous databases and select appropriate datasets for one disease of interest at Benevolent; 
  • Running LVMs, adapting and/or developing other AI models to identify disease-specific mechanisms; 
  • Collaborating with biology experts to analyse and evaluate the results. 
  • Contributing to Python codebases to process and analyse the data

We are looking for someone with

  • A PhD (or should be currently working towards completion of a PhD) in the field of computational biology, bioinformatics or related field with an interest in data science (or vice versa);
  • Familiarity of biomedical datasets and bioinformatics techniques referred to in project descriptions
  • Familiarity in coding with Python and commonly used informatics, data science, machine learning packages
  • Good communication skills who enjoys working in a collaborative team environment


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.

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?

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