Scientist, Computational Medicinal Chemistry

Monte Rosa Therapeutics; Basel; Vor Ort; CHF 80’000 - 120’000; Vollzeit

Zusammenfassung

A biotechnology company in Basel is seeking a motivated Computational Medicinal Chemist to support drug discovery programs. The role involves applying computational techniques to optimize compound design and collaborating with multidisciplinary teams. Applicants should hold a PhD and have 1-4 years of relevant experience in pharmaceutical or biotech sectors. The position emphasizes skills in molecular docking, medicinal chemistry, and computational tools like PyMOL and Schrödinger suite.

Qualifikationen

• PhD with strong computational focus in chemistry, biophysics, or related discipline.
• 1-4 years of postdoctoral or relevant industry experience in drug discovery.
• Experience with ligand- and structure-based design approaches.

Aufgaben

• Support lead identification and optimisation through computational contributions.
• Apply molecular docking and ligand-based design techniques.
• Communicate computational results to project teams effectively.

Kenntnisse

Computational chemistry

Medicinal chemistry

Molecular docking

Python

Data analysis

Statistical analysis

Ausbildung

PhD in computational chemistry or related field

Tools

PyMOL

Schrödinger suite

Jupyter notebooks

Jobbeschreibung

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.

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 development and continuous improvement of computational workflows, tools, and best practices within the realm of computational medicinal chemistry.

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 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.