Computational Chemist - Generative Molecule & Protein Design

Responsibilities

• 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.

• Ph.D. in 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.
• 1+ years of intensive research experience (academic or industry) focused on protein modeling, molecular design, virtual screening, or AI/ML for molecules.
• Hands‑on experience with docking tools, molecular dynamics packages (e.g., GROMACS, AMBER, or OpenMM), and quantum chemistry tools.
• Proficiency in Python (Num Py, Sci Py, Pandas, PyTorch) and practical experience using RDKit for cheminformatics and developing generative molecular models.
• Strong grasp of enzyme kinetics, binding thermodynamics, transition‑state theory, and how synthetic modifications alter macromolecular structures.

Location:

Santa Clara, CA. Salary range: $145,300 - $269,800 annually. (Actual pay determined by experience, qualifications, geographic location, and other job‑related factors permitted by law.)

Benefits: This position qualifies for the benefits detailed in the company information. Relocation benefits are not available.

Roche is an equal‑opportunity employer. We are committed to employing, promoting, and otherwise treating employees and applicants on the basis of merit, qualifications, and competence. This policy prohibits unlawful discrimination, including but not limited to discrimination on the basis of Protected Veteran status, individuals with disabilities, consistent with all federal, state, or local laws.