Monte Rosa Therapeutics (MRT) seeks to recruit an experienced, highly skilled, and creative computational chemist/AI/ML expert to join MRT’s computational chemistry team. You will connect chemistry to biology to rationally design a new class of novel molecular glue degraders (MGDs). The successful candidate will be involved in many aspects of chemistry research activities, interface with team members on the development of unique chemical matter to solve novel biological problems and contribute to the development of our growing program portfolio. You will work tightly with chemistry, biology, and the rest of the data science team to develop, validate and optimize novel chemical matter to treat patients. In this position, you will make significant contributions at the forefront of drug discovery. Monte Rosa is based in Boston and Basel.

• Develop Innovative Computational Methods: Design and implement new computational and machine learning approaches to support rational Molecular Glue Degrader (MGD) design.
• Project Team Leadership: Serve as a critical contributor on project teams, guiding MGD design and optimization by integrating computational techniques such as molecular docking, ligand-based design, diversity and conformational analyses, among others.
• Automation of Discovery Chemistry: Lead efforts to automate early-stage discovery chemistry through a combination of data science, cheminformatics, and AI/ML.
• Compound Collection Strategy: Continuously refine and execute Monte Rosa’s computational strategy for expanding the compound collection to enhance discovery capabilities.
• Large-Scale Data Analysis: Analyze internal high-throughput screening (HTS) data to generate large-scale (SAR) insights, driving hit expansion and supporting the growth of Monte Rosa’s library.
• Strategic Presentation and Guidance: Present findings and strategic insights to project teams, ensuring timely analysis to advance key project objectives.

• PhD in computational chemistry, computer science, AI/ML, or a related discipline solving biological/chemical problems using computational approaches.
• 5+ years of pharmaceutical/biotech industry experience working with small molecules
• Experience using CADD/cheminformatics/ML tools to identify patterns and determine structure-function relationships, including knowledge of relevant databases and tools.
• Proficiency in Python, SQL, and cheminformatics toolkits (OEChem, RDKit, DeepChem) with practical application of these skills.
• Expertise in machine learning libraries (TensorFlow, Keras, PyTorch, Pandas, Scikit-Learn).
• Demonstrated modelling impact on drug design, including experience in ADMET predictions and multiparameter optimization, ligand and structure-based design, conformational analysis, and pharmacophore development.
• Excellent communication skills and the ability to forge productive relationships and collaborations both internally and externally.
• Experience in targeted protein degradation is a plus.