Amgen

biotech

SeniorScientistComputationalProteinDesign

$146–198k Beverly Hills, California, United States FULL TIME
The Brief

“Senior Scientist - Computational Protein Design at Amgen. Skills: Computational Protein Design, ML protein design workflows, scalable pipelines, AI/ML-driven protein design, structure prediction tools. Develop and deploy automated computational pipelines for large-scale binder design. supporting the creation of diverse design candidates and libraries across multiple targets”

What You'll Achieve.

accelerating the generation of molecules used to probe novel biology and deliver new biological insights

Industry & Context.

biotech

What They're Looking For.

Must Have

Doctorate degree PhD OR PharmD OR MD [and relevant post-doc experience in Computational Biology, Structural Biology, Bioengineering, Biophysics, Computer Science, or related discipline with a focus on protein design], Master’s degree and 3 years of protein design experience, Bachelor’s degree and 5 years of protein design experience

Nice to Have

Ph. D. with postdoc in Computational Biology, Structural Biology, Bioengineering, Biophysics, Computer Science, or related discipline with a focus on protein design., Demonstrated experience in computational protein design, including the design of binders such as minibinders and/or antibodies., Experience developing automated and scalable computational pipelines for protein design or structural modeling, ideally in high-throughput environments., Familiarity with modern AI/ML-driven protein design and structure prediction tools (e. g. , AlphaFold, ProteinMPNN, RFdiffusion, or similar frameworks)., programming skills in Python and/or other scripting languages, with experience building maintainable workflows and automation for large-scale computational experiments., Experience working with large protein libraries or multiplexed design strategies, including design filtering, ranking, and diversity optimization., Knowledge of protein structure–function relationships, epitope targeting strategies, and protein–protein interaction design principles., Experience integrating computational design outputs with experimental validation workflows, including library generation, screening, or directed evolution approaches., Familiarity with cloud computing, high-performance computing (HPC), and workflow orchestration tools., Experience collaborating in cross-functional teams spanning computational scientists, experimental biologists, and data scientists., communication skills and ability to contribute to a collaborative protein design community, including sharing tools, best practices, and design insights.

What You'll Do.

Develop and deploy automated computational pipelines for large-scale binder design

supporting the creation of diverse design candidates and libraries across multiple targets

Develop and automate ML protein design workflows for binder generation

Build scalable pipelines for designing large libraries of de novo proteins across multiple targets

Apply computational methods to support multiplexed screening strategies and receptor discovery efforts

Design and prioritize binders for individual targets and large target panels

Contribute to shared tools

and best practices within the protein design community

How You'll Work.

Team & Collaboration

Collaborate closely with experimental scientists and data teams to enable rapid validation and iteration; Experience collaborating in cross-functional teams spanning computational scientists, experimental biologists, and data scientists.; ability to contribute to a collaborative protein design community, including sharing tools, best practices, and design insights.

Communication Scope

communication skills

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