Amgen
biotech
SeniorScientist–DigitalDiscovery:AIassistedAntibodyDiscovery&Data
“Senior Scientist – Digital Discovery: AI-assisted Antibody Discovery & Data at Amgen. Skills: AI-assisted Antibody Discovery, Digital Discovery, Data Generation, experimental translation of AI/ML designs, antibody discovery workflows, high-throughput data generation, BioFoundry integration. Translate AI/ML-generated antibody designs into experimentally testable strategies. Design and execute workflows to express, screen, and characterize AI-derived antibodies”
What You'll Achieve.
enable a closed-loop design–make–test–learn ecosystem for next-generation therapeutics; improve design quality; maximize throughput, reproducibility, and data value
Industry & Context.
problem-solving skills
What They're Looking For.
Must Have
PhD in Biology, Immunology, Immunoengineering, Biochemistry, Bioengineering or related field OR Master’s degree + 3+ years of relevant experience OR Bachelor’s degree + 5+ years of relevant experience
Nice to Have
Experience in antibody discovery and engineering, including display technologies and/or in vivo platforms, Hands-on experience with protein expression, screening, and characterization workflows, Familiarity with high-throughput or automated experimental systems, Exposure to computationally guided or AI-enabled discovery approaches, Experience working with structured biological data, databases, or LIMS systems, Demonstrated ability to work cross-functionally with computational, data science, or engineering teams, scientific communication and problem-solving skills
What You'll Do.
Translate AI/ML-generated antibody designs into experimentally testable strategies
Design and execute workflows to express
and characterize AI-derived antibodies
Partner closely with computational and ML teams to refine hypotheses and improve design quality
Contribute to traditional antibody discovery workflows
including in vivo / immunization-based platforms
Apply comparative approaches to evaluate AI-designed vs. conventionally derived antibodies
Help define best practices for integrating next-generation and established discovery paradigms
Develop and implement pipelines for systematic data capture
Generate high-quality sequence–function datasets to support model training and benchmarking
Ensure experimental outputs are structured
Work with automation and platform teams to enable scalable
high-throughput validation workflows
Contribute to the development of a BioFoundry-enabled discovery engine
Help define experimental designs that maximize throughput
How You'll Work.
Team & Collaboration
Partner closely with computational and ML teams; Work with automation and platform teams; Demonstrated ability to work cross-functionally with computational, data science, or engineering teams
Communication Scope
scientific communication
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