About the Role
BenevolentAI is seeking to hire a talented AI Scientist to contribute to the development of our industry-leading AI models. At BenevolentAI, we harness the power of artificial intelligence (AI) and human expertise to revolutionise the field of drug discovery. Our unique computational R&D platform, combined with our in-house pipeline of drug programmes, enables us to develop new and more effective medicines. As an AI Scientist, you will perform research to develop state-of-the-art solutions around the core problems we work on at BenevolentAI. In particular, you will focus on methods to address crucial challenges in end-to-end drug discovery, for example, using multimodal data to identify the best target to modulate in order to treat a disease, or modelling the molecular properties and structures of compounds that can modulate that target.
Responsibilities
- Apply your expertise in machine learning to research new solutions to important problems in drug discovery
- Work as a member of a cross-functional team comprising specialists in informatics, engineering, AI and drug discovery to develop new capabilities and improve existing products
- Keep up-to-date with the latest research and progress in machine learning for drug discovery
- Work with machine learning engineers to help translate research prototypes into practical solutions for BenevolentAI's products and platform
- Follow robust software development best practices
- Contribute to writing papers for journals and at conferences
- Contribute to our thoughtful, collaborative, and ambitious culture
- Propose novel machine learning projects and research directions that can better address important challenges in drug discovery
- Promote machine learning best practices, such as: scalable training and deployment, in-depth model introspection and evaluation, new state-of-the-art methods, and so on
- Identify opportunities for publications
- Represent BenevolentAI externally at conferences and events
Requirements
- An advanced degree (Masters or PhD) in machine learning, computer science, or a related field with a clear focus on empirical research
- Strong knowledge of modern machine learning methods and techniques (e.g. transformers, LLMs, GNNs, etc.)
- Strong proficiency with Python
- Knowledge of modern tools for machine learning, including frameworks such as PyTorch
- Experience building research prototypes and developing product-worthy tools from them
- Strong communication skills: ability to communicate complex machine learning concepts to a broad audience
- Ability to work independently as well as part of a team
- Bonus points if you have experience applying machine learning in drug discovery or related fields, and/or knowledge of core problems in drug discovery and development