Computational Chemist - Generative Molecule & Protein Design

About the role

A healthier future. It’s what drives us to innovate. To continuously advance science and ensure everyone has access to the healthcare they need today and for generations to come. Join Roche, where every voice matters.

Opportunity

• Drive Molecular & Protein Design: Build and run structure-based and ligand-based virtual screening workflows to find new substrates, cofactors, and small molecules for our sequencing and biocatalysis platforms
• Enzyme Modeling & De Novo Design: Perform advanced structural modeling and molecular docking simulations on natural and engineered enzyme variants, with a heavy focus on optimizing multi-ligand binding pathways. Lead in silico de novo enzyme design, creating novel protein scaffolds and active sites tailored for multi-ligand binding, optimal catalysis, and enhanced structural stability
• Simulate Molecular Dynamics: Explore conformational changes, reaction mechanisms, transition states, and electronic structures using advanced physics-based modeling and quantum chemistry tools
• Use Computational Tools: Analyze and optimize biopolymers and biomimetic polymers, leveraging rich internal datasets to design new derivatives and tune properties relevant to sequencing and diagnostic performance
• Advance Generative AI Pipelines: Develop and scale generative workflows (including Transformers, GNNs, and diffusion models) for property-guided molecule generation and Computer-Aided Synthesis Planning (CASP)
• Pilot Emerging Technologies: Scout and implement cutting-edge tools from the literature and the vibrant local AI ecosystem into production-grade workflows

Qualifications

• You are a curious, collaborative, and driven scientist who loves combining physics-based modeling with modern machine learning to solve complex biological puzzles
• You explain complex models clearly to diverse teams, value reproducible research, and are excited to co-design experiments that bridge the digital and physical worlds
• You have a Ph.D. Computational Chemistry, Biochemistry, Biophysics, Structural Biology, or a highly quantitative related field or a Master’s degree in Computational Chemistry, Biochemistry with 2 years of related experience or Bachelors with 3 years of related experience
• You have a 1+ years of intensive research experience (academic or industry) focused on protein modeling, molecular design, virtual screening, or AI/ML for molecules
• You have hands-on experience with docking tools, molecular dynamics packages (such as GROMACS, AMBER, or OpenMM), and quantum chemistry tools
• You are proficient in Python (NumPy, SciPy, Pandas, PyTorch) combined with practical experience using RDKit for cheminformatics and developing generative molecular models
• You have a strong grasp of enzyme kinetics, binding thermodynamics, transition-state theory, and how synthetic modifications alter macromolecular structures

Skills

• Proficiency in Python (NumPy, SciPy, Pandas, PyTorch)
• Practical experience using RDKit for cheminformatics
• Experience with docking tools, molecular dynamics packages (such as GROMACS, AMBER, or OpenMM), and quantum chemistry tools
• Hands-on experience with generative workflows (including Transformers, GNNs, and diffusion models)
• Strong understanding of enzyme kinetics, binding thermodynamics, transition-state theory, and synthetic modifications

Benefits

• Relocation benefits are not available for this position

Pay

The expected salary range for this position is based on the primary location of Santa Clara, CA is $145,300 - $269,800 Annual. Actual pay will be determined based on experience, qualifications, geographic location, and other job-related factors permitted by law. A discretionary annual bonus may be available based on individual and Company performance.