Senior Scientist (m​/f​/d), Computational Pathology Biomarker Lead (Oncology

About Astrazeneca

AstraZeneca is a global, science-led, patient-focused biopharmaceutical company that focuses on the discovery, development and commercialisation of prescription medicines for some of the world’s most serious diseases. But we’re more than one of the world’s leading pharmaceutical companies.

SITE DESCRIPTION - Munich, Germany

At Computational Pathology Munich (CPM), we make a significant contribution to high-performance, data-driven research and development. Our team operates in a demanding, fast-paced environment where excellent collaboration, clear communication and precise organization are critical.

About Astrazeneca

AstraZeneca is a global, science-led, patient-focused biopharmaceutical company that focuses on the discovery, development and commercialisation of prescription medicines for some of the world’s most serious diseases. But we’re more than one of the world’s leading pharmaceutical companies.

SITE DESCRIPTION - Munich, Germany

At Computational Pathology Munich (CPM), we make a significant contribution to high-performance, data-driven research and development. Our team operates in a demanding, fast-paced environment where excellent collaboration, clear communication and precise organization are critical.

BUSINESS AREAAstraZeneca’s Enterprise AI organization is shaping the future of drug development with an integrated AI engine that connects data, technology, and expertise to accelerate breakthroughs. In Computational Pathology and Biomarkers, we deliver AI-driven solutions for patient selection, biomarker development, and clinical decisions on a scale. We collaborate across the organization to reuse capabilities and scale innovation globally measuring success by adoption, impact, and measurable outcomes across therapeutic areas and regions.

Do you thrive at the intersection of AI innovation and clinical translation? Do you bring expertise in leading cross-functional teams and a passion for driving innovation? Would you like to contribute to the Oncology strategic vision in a company that follows the science and turns ideas into life-changing medicines?

We are looking for a

Senior Scientist (m/f/d), Computational Pathology Biomarker Lead (Oncology)

to drive the development of AI-enabled computational pathology and multimodal biomarkers that transform patient selection and drug development across our Oncology portfolio. This role is based at our Munich, Germany office.

In this role, you will collaborate with multidisciplinary teams to pioneer data-driven approaches that generate impactful insights and improve clinical outcomes. You will contribute to an industry-leading portfolio of targeted therapy programs, from early development through to lifecycle management of marketed therapies.



Key Responsibilities

Contribute scientific expertise in AI-powered computational pathology and multimodal biomarker development for AstraZeneca’s Oncology portfolio, delivering robust biomarkers that enable patient selection and inform drug development decisions. Working at the intersection of data, AI innovation, and tumor biology, you will collaborate in cross-functional teams to develop and implement computational pathology solutions from early discovery through clinical validation, generating high-quality translational insights that support critical decisions and advance precision medicine.

• Lead and collaborate with cross-functional teams to generate digital biomarker signatures from complex datasets using AI/machine learning, enabling target engagement assessment, patient stratification, and early signals of biological activity.
• Drive biomarker discovery, development, and implementation across Oncology programs, using advanced computational pathology technologies to guide indication selection and identify target patient populations.
• Apply deep understanding of cancer biology to interpret clinical samples, support rational drug combinations, and identify mechanisms of resistance.
• Use strong statistical and analytical expertise to develop novel image-derived metrics and uncover meaningful patterns in complex, multimodal datasets.
• Integrate tissue, imaging, genomics, and clinical data to inform…