Scientist, Computational Medicinal Chemistry

Overview

We are seeking a highly motivated, creative Computational Medicinal Chemist to support drug discovery programs. The successful candidate will operate at the interface of computational chemistry and medicinal chemistry, serving as an embedded, project-facing contributor within lead identification and lead optimisation (LI/LO) teams. The position will also involve contributions to earlier drug discovery phases and the development of computational tools with direct application in medicinal chemistry.

This role is strongly project-driven: you will apply computational approaches to directly inform compound design, optimisation, and decision-making, working closely with multidisciplinary teams in chemistry, biology, and data science. The position offers the opportunity to make a tangible impact on the design and optimisation of novel chemical matter, leveraging the company’s core expertise in degrader discovery.

• Serve as a core computational contributor on project teams, supporting lead identification, hit-to-lead, and lead optimisation through structure- and ligand-based design.
• Apply and integrate computational techniques such as molecular docking, ligand-based design, diversity and conformational analyses, molecular modelling, and related approaches to guide SAR exploration and compound optimisation.
• Contribute to the design and prioritisation of project-relevant compound libraries and collections in close collaboration with medicinal chemists.
• Communicate computational results clearly and effectively to cross-functional teams, translating analyses into actionable medicinal chemistry guidance.
• Contribute to the development and continuous improvement of computational workflows, tools, and best practices within the realm of computational medicinal chemistry.

• PhD in computational chemistry, chemistry, biophysics, or a related scientific discipline with a strong computational focus.
• 1-4 years of Postdoctoral training and/or relevant industry experience in pharmaceutical or biotech drug discovery.
• Demonstrated application of ligand- and structure-based design approaches in small-molecule drug discovery projects.
• Working knowledge of medicinal chemistry and preclinical drug design in the context of compound optimisation, including SAR development, ADME considerations, and multiparameter optimisation.
• Solid understanding of protein–ligand interactions and structure-based compound optimisation strategies, along with hands‑on experience with multiple core computational techniques in ligand- and structure-based drug design.
• Hands‑on experience with molecular visualisation and modelling software such as PyMOL and Schrödinger suite for structure analysis and drug design applications.
• Proficiency in Python and cheminformatics toolkits with practical application of these skills for scientific scripting, data analysis, workflow development, and management and analysis of large chemical datasets.
• Proficiency in statistical analysis and data visualisation tools (e.g. Jupyter notebooks, Spotfire).
• Familiarity with machine‑learning approaches for small-molecule activity and ADME property prediction, and experience applying model outputs in a medicinal chemistry or project context.
• Experience working effectively within multidisciplinary project teams and communicating computational results to non‑computational scientists.
• Strong scientific writing skills and track record of publications in peer-reviewed journals.
• Experience in targeted protein degradation is a plus.