AstraZeneca

AstraZeneca

Postdoctoral Fellow – Explore epigenetic mechanisms of anti-cancer drug resistance

Cambridge MA – 100 Binney Street · Junior

Sponsorship not specifiedDetected 2 days ago
Data SciencePharmacologyqPCRCRISPRMolecular BiologyCell CultureResearchProtein AnalysisWestern BlottingAnimal StudiesCollaboration

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About the role

  • Postdoctoral Fellow – Explore epigenetic mechanisms of anti-cancer drug resistance
  • Competitive Salary, Bonus & Benefits Package

Responsibilities

  • Our Postdoctoral Fellow will lead a three-year research project on the epigenetic basis of resistance to targeted therapy in lung cancer.
  • Apply epigenomic and transcriptomic profiling (e.g. RNA-seq, ATAC-seq, ChIP-seq or CUT&RUN) to identify the pathways and genes that drive resistance, and validate them using genetic and pharmacological approaches.
  • Lead the project in collaboration with the cross-functional AstraZeneca team and our academic collaborators.
  • AstraZeneca's Postdoc Program is for self-motivated individuals looking to deliver exciting projects in an encouraging, engaging, and innovative environment.
  • By defining how epigenetic mechanisms drive this resistance and testing new combination strategies, you will generate insights with the potential to change treatment for patients with few options.
  • AstraZeneca is a global, science-led, patient-centered biopharmaceutical company focusing on discovering, developing, and commercializing prescription medicines for some of the world's most serious diseases.
  • 03-Nov-2026 Our mission is to build an inclusive environment where equal employment opportunities are available to all applicants and employees.

Requirements

  • PhD degree in cancer biology, molecular biology or a related field, either awarded within the last 4 years, or due to be awarded within 6 months of joining AstraZeneca
  • Strong understanding of cancer biology and mechanisms of resistance to targeted therapy
  • Hands-on experience with mammalian cell culture, cell-based assays (e.g. proliferation/viability, western blot, qPCR) and genetic manipulation of cells (e.g. CRISPR knockout, overexpression or knockdown)
  • Experience with in vivo mouse tumour models (e.g. xenograft or patient-derived xenograft)
  • Hands-on experience with epigenomic assays (e.g. ChIP-seq/CUT&RUN, ATAC-seq)
  • Compensation for this role, based on years of experience after obtaining PhD, is a minimum of $99,900 up to a maximum of $120,000 + short-term incentive.

Nice to have

  • Postdoctoral Fellow - Explore epigenetic mechanisms of anti-cancer drug resistance
  • Are you a cancer biologist fascinated by how tumours escape targeted therapy?
  • Then join Oncology R&D at AstraZeneca and unlock the power of what science can do!
  • About the opportunity
  • Your work will focus on lung cancer, where resistance to targeted treatment remains a major unmet need.
  • You will join the Small Molecule Bioscience team within Oncology Targeted Discovery (OTD) in Cambridge, MA.
  • You will work alongside project teams, epigenetics and data science experts, and an academic mentor, in a collaborative environment where your findings can shape future drug discovery.
  • This project explores how epigenetic changes allow lung cancer cells to escape targeted therapy.

Compensation

  • for this role, based on years of experience after obtaining PhD, is a minimum of $99,900 up to a maximum of $120,000 + short-term incentive.

Benefits

  • Resistance to targeted therapy limits the benefit for many lung cancer patients.

Company info

  • At AstraZeneca, we're dedicated to being a Great Place to Work and empowering employees to push the boundaries of science and fuel their entrepreneurial spirit.
  • Bring your expertise, apply your knowledge, follow the science, and make a difference.

Equal opportunity

  • If you have a disability or special need that requires accommodation, please complete the corresponding section in the application form.

This listing is sourced directly from AstraZeneca's careers page and normalized into a canonical job model.