About this role
Salary: £60,000 - 100,000 per year
Requirements: At least 4 years of significant experience innovating, developing, deploying, and continuously supporting machine learning data management and modeling.Strong hands-on coding proficiency in Python and deep learning frameworks.Strong understanding of and experience with version control systems such as GitHub, Git, Subversion, or Bitbucket.Demonstrated expertise in several molecular AI/ML areas, including generative chemistry; structure-based drug design; protein-ligand modeling and co-folding; docking, scoring, and pose assessment; QSAR; multi-objective property optimization; uncertainty estimation; active learning; and free-energy and affinity prediction.Demonstrated experience with AI-driven molecular design.Curiosity and passion for biomedical sciences and therapeutics discovery.Ability to assess emerging technologies pragmatically and identify how they can be integrated into business solutions.Ability to balance requirements, manage expectations, and deliver results proactively, including identifying and resolving issues.Strong organizational and problem-solving skills, with the ability to execute and prioritize in a complex, matrixed environment.Strong interpersonal and communication skills, including the ability to explain analytical concepts to diverse audiences and stakeholders; English is our primary language.A respectful, collaborative team-player attitude.Desired expertise includes molecular representation learning for small molecules, graph neural networks, geometric deep learning, ADME/PK and physicochemical property prediction, safety, de novo design, chemical-space exploration, chemistry foundation models, uncertainty quantification, active learning, agentic AI, generative chemistry, counterfactuals and explainability, and multi-objective optimization.Experience in a large research organization and a deep understanding of drug development are advantageous. Responsibilities: Contribute to the conceptualization and application of AI methods for hit generation, lead optimization, and preclinical analysis, including safety and PK/PD.Develop, adapt, and evaluate state-of-the-art AI and machine learning models, including foundation models, generative AI, multimodal AI, and agentic systems.Establish rigorous evaluation and benchmarking frameworks to assess model robustness and scientific validity in drug discovery.Define translatable metrics that connect model performance with downstream scientific decisions, including assay-level or prioritization improvements and experimental efficiency.Help integrate AI approaches into design-make-test-analyze cycles to accelerate low-molecular-weight drug discovery.Work with Engineering and Product Development teams to support delivery of AI solutions.Communicate progress and impact to stakeholders and multidisciplinary audiences.Engage and align regularly with AI4R teams, the broader data science community, and senior scientists.Collaborate with medicinal chemists, DMPK, structural biology and disease-area scientists, engineers, and other AI experts to apply AI approaches to low-molecular-weight drug discovery. Technologies: Agentic AIAIBitBucketGitGitHubSupportMachine LearningPython More:
We are seeking a Senior Expert in Applied AI, Low Molecular Weight Drug Discovery, within Novartiss Applied AI, Low Molecular Weight group of AI4R. In this role, you will contribute to AI methods and workflows for drug discovery as part of a global team of AI researchers and subject-matter experts, working with multidisciplinary project teams. The position is based in Cambridge, USA, is full time, and follows a hybrid schedule of three days per week in the office. The stated annual salary range is $138,600 to $257,400 USD. We are an equal opportunity employer and are committed to providing reasonable accommodations to individuals with disabilities.
last updated 40 week of 2026