Senior Scientist (mfd), 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 worlds most serious diseases. But were more than one of the worlds 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 AREA
AstraZenecas Enterprise AI organization is shaping the future of drug development with an integrated AI engine that connects data technology and expertise to accelerate 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 AstraZenecas 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 project strategy and clinical decision-making.

• Support analytical validation frameworks for multimodal biomarkers enabling regulatory submissions and clinical implementation.

• Contribute to project quality through data review reporting presentations publications and input into clinical and regulatory documents.

• Support vendor selection companion diagnostics development and biomarker strategies for clinical studies.

• Drive innovation by evaluating and implementing new AI technologies and improving computational pathology workflows.

• Share expertise by training peers promoting reproducible research and contributing to the external scientific community.

• Lead scientific discussions and present progress and insights to project teams and leadership.

Experience and Capabilities

Essential

• PhD in Biological Sciences Computational Biology Bioinformatics or a related field with demonstrated experience at the interface of biology and data science.

• Strong expertise in computational pathology and AI-driven image analysis particularly histopathology with hands-on implementation experience.

• Deep understanding of cancer biology including tumor microenvironment immune pathways and mechanisms of resistance.

• Proven ability to generate insights from complex multi-modal datasets including tissue imaging genomic and clinical data.

• Proficiency in programming (Python/R) and advanced data analysis including clinical biostatistics (e.g. survival analysis feature selection cross-validation visualization).

• Experience with data management best practices including curation data engineering FAIR principles and reproducible research.

• Solid understanding of clinical trials and oncology drug development with experience contributing to clinical research strategies.

• Strong collaboration and influencing skills with the ability to work effectively in cross-functional fast-paced environments.

• Excellent scientific communication skills with the ability to present complex data clearly to both specialist and non-specialist audiences.

• Outstanding analytical organizational and problem-solving capabilities.

• Ability to prioritize effectively remain highly productive and balance innovation with timely project delivery in a dynamic environment.

• Demonstrated success contributing to interdisciplinary cross-functional projects.

Desirable

• Experience in the pharmaceutical or biotechnology industry particularly in translational medicine or biomarker development.

• Hands-on experience applying machine learning/AI approaches to image analysis and biomarker discovery.

• Understanding of clinical trial design biomarker validation strategies and regulatory requirements for AI-enabled biomarkers.

• Proven publication record in peer-reviewed journals demonstrating expertise in computational pathology and/or AI.

• Formal training in computational biology bioinformatics data science AI or machine learning.

• Familiarity with approaches for integrating multimodal biomarkers.

What you can expect:

• Individual development opportunities with a focus on lifelong learning

• Trust appreciation and room to shape things in a focused and passionate team

• Modern office space in Munich enabling collaborative flexible and agile work

• A diverse inclusive and bias-free work environment actively welcoming applications from all qualified candidates regardless of background or characteristics

Date Posted

Closing Date

AstraZeneca embraces diversity and equality of opportunity. We are committed to building an inclusive and diverse team representing all backgrounds with as wide a range of perspectives as possible and harnessing industry-leading skills. We believe that the more inclusive we are the better our work will be. We welcome and consider applications to join our team from all qualified candidates regardless of their characteristics. We comply with all applicable laws and regulations on non-discrimination in employment (and recruitment) as well as work authorization and employment eligibility verification requirements.