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.
You will be responsible for developing and executing an applied research agenda around the core problems we work on at BenevolentAI, with a focus on inferring disease therapies via novel drugs. As an AI scientist, this could include working on: Knowledge graph inference, Unsupervised representation learning, Generative modelling and/or Natural Language Processing (i.e. Large language models, Name Entity Recognition, etc) depending on your expertise and interests.
- Implement new state of the art models in frameworks such as Pytorch, to solve core problems in the end to end drug discovery process.
- Stay up to date with the latest ML research through publications and conference attendance (i.e. Neurips, ICLR, ICML, etc).
- Develop new approaches to evaluate the performance of AI and ML models in relation to key business objectives.
- Work as a member of a cross-functional team comprising specialists in informatics, engineering, AI, drug discovery and product. In these teams, you will apply your expertise in artificial intelligence and machine learning to develop tools for drug discovery and development in an applied research setting.
- Work with machine learning engineers to help bring research prototypes and features into BenevolentAI’s product portfolio.
We are looking for someone with:
- MSc degree or PhD in machine learning, computational biology or any other relevant quantitative discipline.
- Hands-on experience with commonly used ML frameworks such as Pytorch or Tensorflow.
- Strong software engineering practices such as familiarity with Git and Continuous Integration.
- Experience building research prototypes and familiarity with developing product-worthy tools from them.
- Enjoys working in a fast-paced, highly-collaborative environment.
- Strong communication skills.
- Experience applying machine learning techniques to genomic data such as transcriptomics or proteomics.
- Knowledge of the pharmaceutical industry with a focus on drug discovery.Bonus points for having experience applying machine learning to biological problems
- Bonus points for any of the following: experience working with knowledge graph models such as link prediction for automated reasoning from a knowledge base, ML applied to genomics data (i.e. Unsupervised learning), handling and modelling clinical datasets.
BenevolentAI unites AI with human expertise to discover new and more effective medicines. Our unique computational R&D platform spans every step of the drug discovery process, powering an in-house pipeline of over 25 drug programmes. We advance our mission to reinvent drug discovery by harnessing the power of a diverse team, rich with different backgrounds, experiences, opinions and personalities. In our offices in London and New York and research facility in Cambridge (UK), we work in highly collaborative, multidisciplinary teams, harnessing skills across biology, chemistry, engineering, AI, machine learning, informatics, precision medicine and drug discovery.
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.
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 think about life at Benevolent. You can also find out more about us on LinkedIn and Twitter.