Director, Team Lead, Computational Pathology Biomarker Development (Oncology/BioPharmaceuticals) (m/f/d)
Do you thrive at the intersection of AI innovation and clinical translation? Do you have expertise in, and a passion for leading cross functional teams to drive innovation? Would you like to apply your expertise to impact the Oncology and/or BioPharma strategic vision in a company that follows the science and turns ideas into life changing medicines? Then AstraZeneca might be the one for you! In this position you will work with a multi-disciplinary team to pioneer AI-enabled computational pathology and multi-modal biomarkers that fundamentally change how we approach patient selection and drug development, aiming to improve clinical. You will have the opportunity to impact an industry-leading portfolio of diverse therapeutic programs from inception through to life cycle management for marketed drugs. This role is based at our Munch, Germany office.
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 building the future of drug development, a fully integrated AI engine that connects data, technology, and expertise to accelerate breakthroughs across our portfolio. Within AI for Computational Pathology and Biomarkers, we're pioneering AI-powered solutions that transform patient selection, biomarker development, and clinical decision-making at enterprise scale. We thrive on collaboration: actively leveraging capabilities across the organization, promoting reuse, and scaling innovations from concept to global impact. Our measure of success isn't just innovation—it's adoption, scale, and tangible results across therapeutic areas and geographies.
Key Responsibilities
Provide strategic scientific leadership for AI-powered computational pathology and multimodal biomarker development across AstraZeneca's Oncology and/or BioPharmaceuticals portfolio, delivering robust biomarkers that enable patient selection from target validation through life cycle management. Lead, develop, and inspire a high-performing team of Biomarker Leads while directing cross-functional matrix teams to implement strategic vision with end-to-end ownership toward clinical implementation. Operating at the convergence of data, AI innovation, and biology, develop reusable biomarker platforms that may travel with biological mechanisms across disease continuums. Deliver high-impact insights that inform critical drug development decisions, shape portfolio strategy, and enable regulatory submissions and clinical operationalization.
- Provide direct line management for a team of Computational Pathology Biomarker Leads including talent development, performance coaching, career progression planning, and fostering a culture of scientific excellence, collaboration, and innovation that enables team members to deliver their best work and grow their capabilities.
- Provide strategic scientific leadership in AI-powered computational pathology, biomarker discovery, development, and translational science, working with multiple cross-functional teams across the Oncology and/or BioPharmaceuticals portfolio to deliver transformative biomarkers from target validation through clinical implementation.
- Develop and implement strategic vision for AI-powered computational pathology with end-to-end accountability, enabling target identification, indication selection, early indication of biological activity, and patient stratification/selection across multiple programs.
- Oversee proof-of-concept studies by integrating AI-enabled computational pathology with imaging, blood biomarkers, genomics, proteomics, and clinical data to understand key disease pathways and mechanisms, guide rational drug combinations, define resistance mechanisms, and provide expert strategic advice that shapes portfolio decisions and patient selection strategies.
- Lead and build high-performing cross-functional teams of pathologists, biomarker scientists, data managers, biologists, AI imaging scientists, program managers and data scientists to drive computational pathology input throughout the drug/biomarker development process with alignment on implementation strategies.
- Drive innovation in AI-powered biomarker development by establishing quantitative composite scores, disease progression trajectory models, spatial biomarker signatures, and novel metrics from images that capture organ-specific pathology patterns and enable trial enrichment, patient stratification, and alternative endpoint strategies that accelerate clinical timelines.
- Develop strategic approaches for reusable biomarker platforms that function as platform assets across multiple indications sharing common biological mechanisms, traveling with biological pathways across disease continuums.
- Establish analytical and clinical validation frameworks for multimodal biomarkers with strategic emphasis on regulatory readiness, supporting regulatory submissions, companion diagnostics development, and clinical operationalization.
- Champion AI innovations and disruptive technologies, assess existing processes and workflows for ongoing improvements, and define strategic initiatives that align with departmental and portfolio objectives, contributing to functional and business scientific strategy.
- Function as scientific and AI thought-leader inside and outside the company, serving as key link to external scientific, medical, AI technology, and regulatory communities through strategic collaborations, high-quality publications, and partnerships that establish AstraZeneca's leadership in AI-powered computational pathology.
Experience and Capabilities
Essential
- Direct line management experience with responsibility for team development, performance management, and career progression. Extensive matrix team leadership experience with demonstrated ability to build and lead high-performing cross-functional teams at the data-AI-biology interface with end-to-end implementation focus.
- PhD in Biological Sciences, Computational Biology, Bioinformatics, and/or related fields with extensive experience at the interface of biological sciences, data science, and AI/computer science disciplines.
- At least 5 years of pharmaceutical or biotechnology industry experience in biomarker discovery, translational research, and companion diagnostics, preferably in Oncology and/or BioPharmaceuticals research areas.
- Recognized expertise in computational pathology methods and advanced AI-powered image analysis with track record of innovation and implementation, particularly in histopathology image analysis applications.
- Deep understanding of disease biology and mechanisms relevant to Oncology and/or BioPharmaceuticals Therapy Areas, including tumor microenvironment, immune checkpoint pathways, resistance mechanisms, tissue-specific pathology (fibrosis, inflammation, protein deposition, organ damage patterns), and platform biology concepts across disease continuums.
- Experience with diverse therapeutic modalities including antibody drug conjugates, CAR-T cells, T cell engagers, and emerging modalities, with understanding of how computational pathology and AI-powered biomarkers enable patient selection and response monitoring across different drug classes.
- Exceptional capability in handling and extracting insights from complex, multi-dimensional datasets across multiple data modalities, with proven ability to integrate tissue, imaging, blood biomarkers, genomic, and clinical data.
- Deep expertise in translational data science with proven ability to connect AI-powered computational analyses to biological mechanisms, disease progression trajectories, clinical outcomes, and strategic decisions, including advanced proficiency in data analysis methods and programming (Python/R) with applied knowledge of clinical biostatistics.
- Thorough understanding of clinical trials and clinical research strategies with detailed experience in drug development and biomarker implementation pathways across Oncology and/or BioPharmaceuticals programs.
- Proven communication, presentation, and influencing skills at senior leadership levels with ability to articulate AI value proposition and implementation strategies to both specialist and non-specialist audiences.
- Outstanding analytical, research, and organizational skills with excellent problem-solving capabilities, clear understanding of the balance between innovation, smart risk-taking, fit-for-purpose solutions, and timely project delivery, and track record of consistent delivery and impact on drug development programs through AI innovation and successful biomarker implementation.
Desirable
- Demonstrated experience with analytical and clinical validation of AI-enabled biomarker assays for regulatory submissions, companion diagnostics development, and clinical operationalization, including regulatory agency interactions.
- Experience developing innovative biomarker strategies including trial enrichment approaches, quantitative composite scores for organ pathology, and alternative endpoints that accelerate clinical timelines.
- Strong publication record in high-quality scientific journals showcasing AI innovation and biomarker implementation, with active contributions to the research community through conferences, open-source code projects, and leadership in professional organizations and scientific communities focused on AI in healthcare and drug development.
- Proven ability to act as an external ambassador with extensive network of academic collaborators, AI technology providers, industry partners, and regulatory agencies to influence external organizations and enhance the image and reputation of AstraZeneca.
- Formal training in computational biology, bioinformatics, data science, AI, or machine learning with hands-on coding experience in Python, R, or similar programming languages, and deep understanding of AI governance, responsible AI practices, and ethical considerations in healthcare AI applications.
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
19-Mai-2026
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.
