At Roche Sequencing Solutions, we are building the next generation of sequencing and diagnostic platforms powered by advanced computation and AI. As part of our Computational Science & Informatics Chapter, you will sit at the intersection of computational chemistry, structural biology, and applied AI to directly impact real-world commercial instruments and R&D workflows.

The Opportunity

You will join an innovative, collaborative environment where you will:

• 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).

• Collaborate for Impact: Partner closely with experimental wet-lab biochemists, protein engineers, and synthetic chemists to turn computational insights into real-world experiments.

• Pilot Emerging Technologies: Scout and implement cutting-edge tools from the literature and the vibrant local AI ecosystem into production-grade workflows.

Who You Are

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 a Ph.D. Computational Chemistry, Biochemistry, Biophysics, Structural Biology, or a highly quantitative related field or a Master6#8217;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.

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.

This position also qualifies for the benefits detailed here:

Relocation benefits are not available for this position