Job Description

Overview:

We are seeking a highly motivated and creative Computational Medicinal Chemist to support 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, with additional involvement in earlier discovery phases.


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 degrader discovery.


Responsibilities:
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 continuous improvement of computational workflows, tools, and best practices.

Qualifications:
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 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. Proficiency in Python and cheminformatics toolkits with practical application of these skills

for scientific scripting, data analysis, and workflow development

.

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. * Experience in targeted protein degradation is a plus