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Director, Oncology Research

United States, South San Francisco Employment contract 215300.75 - 291289.25 USD / Year · Job Posted May 14, 2026
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Job Description

Let’s do this. Let’s change the world. Amgen is a leader in the discovery and development of innovative cancer therapeutics. The Oncology Research team seeks a Director of Research to develop and lead a portfolio of antibody-based therapeutics for solid tumors. In this role, you will work cross-functionally to implement and advance next-generation approaches for cancer therapeutics. The ideal candidate will have direct experience leading oncology T-cell engager programs from discovery to development candidate nomination, with experience using translational biology approaches to inform clinical development. A deep and broad understanding of cancer cell biology, including human genetics, cell growth signaling pathways, mechanisms of response and resistance, and translational pharmacology will be essential. You will be responsible to lead project teams and external collaborations, as well as to inspire and develop a creative, dedicated research team. You will be an exceptional scientific leader who can translate strategy to execution in a fast-paced, changing matrixed environment. This role has the potential for high visibility within Amgen and externally.

Job Responsibility

  • Lead preclinical research for T-cell engager clinical programs and external collaborations, focused on lung and neuroendocrine cancer
  • Build and lead a portfolio of innovative research programs focused on bispecific antibodies
  • Mentor a team of project leaders and lab-based scientists to discover new biology, deliver robust datasets and make critical decisions for therapeutic programs and technology platforms
  • Contribute to the identification and evaluation of external research opportunities, including business development partnerships and academic collaborations
  • Partner effectively with peers across research and development to advance new science and integrate technology with tumor cell biology, including application of AI/ML approaches to target evaluation and biomarker discovery

Requirements

  • Doctorate degree in Cancer Biology, Cell Biology, Genetics, or related field and 5 years of directly related experience
  • OR Master's degree in Cancer Biology, Cell Biology, Genetics, or related field and 8 years of directly related experience
  • OR Bachelor's degree in Cancer Biology, Cell Biology, Genetics, or related field and 10 years of directly related experience

Nice to have

  • Doctoral degree in Cancer Biology, Cell Biology, Genetics, or related field with at least 12 years of experience in industry following completion of postdoctoral training
  • Deep understanding of lung cancer biology
  • Direct experience leading T-cell engager research programs from target identification and validation to clinical candidate selection and submission of IND/CTA
  • Demonstrated understanding of preclinical dataset required for development candidate nomination, and experience interacting with regulatory authorities
  • Knowledge of antibody engineering approaches, with direct experience designing and evaluating modalities including T-cell engagers and antibody-drug conjugates
  • Experience developing translational biology datasets and interpreting clinical biomarker data
  • Demonstrated ability to use AI/ML to accelerate research and translational biology
  • Demonstrated high scientific impact through publications, invited talks and patents
  • Pragmatic, empathetic leadership style that is inclusive, develops talent, and prioritizes work aligned with our mission to serve patients

What we offer

  • Comprehensive employee benefits package including Retirement and Savings Plan with generous company contributions, group medical, dental and vision coverage, life and disability insurance, and flexible spending accounts
  • Discretionary annual bonus program or sales-based incentive plan
  • Stock-based long-term incentives
  • Award-winning time-off plans
  • Flexible work models where possible

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