Machine Learning Engineer
Associate Director (m/f/d), Computational Pathology Biomarker Lead (Oncology/BioPharma)
Munich
Apply on the employer's siteRole description
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 outcomes. You will have the opportunity to impact an industry-leading portfolio of targeted therapy programs from inception through to life cycle management for marketed drugs.
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 AREA
AstraZeneca'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 scientific leadership for AI-powered computational pathology and multimodal biomarker development across AstraZeneca's Oncology and/or BioPharmaceuticals portfolio, delivering biomarkers that support patient selection and translational decision-making from target validation through clinical development.
- Partner with cross-functional teams to develop and implement biomarker strategies that generate actionable insights and enable clinical implementation.
- Develop and execute biomarker strategies leveraging AI-powered computational pathology to support target identification, indication selection, biological understanding, and patient stratification across multiple drug development programs.
- Design and deliver proof-of-concept studies integrating computational pathology with imaging, blood biomarkers, genomics, proteomics, and clinical data to generate translational insights into disease biology, treatment response, and resistance mechanisms.
- Lead cross-functional biomarker discovery activities in collaboration with pathologists, biomarker scientists, data scientists, biologists, clinicians, and program teams to ensure successful biomarker development and implementation.
- Contribute to innovation in AI-enabled biomarker development through the application of quantitative image-based biomarkers, spatial biology approaches, multimodal data integration, and novel analytical methodologies.
- Support the development of reusable biomarker approaches and platform capabilities that can be applied across programs, indications, and therapeutic modalities.
- Contribute to analytical and clinical validation strategies for multimodal biomarkers, supporting regulatory submissions, companion diagnostic development, and clinical implementation activities.
- Evaluate emerging technologies, AI methodologies, and scientific opportunities to advance computational pathology capabilities and strengthen portfolio impact.
- Represent Computational Pathology in internal and external scientific interactions, contributing to publications, conference presentations, collaborations, and scientific partnerships.
Essential
Experience & Qualifications
- PhD in Biological Sciences, Computational Biology, Bioinformatics, Data Science, Computer Science, or a related discipline, with significant experience working at the intersection of biology, translational medicine, and quantitative data science.
- Significant experience in pharmaceutical, biotechnology, or translational research environments with a strong track record in biomarker discovery, development, and implementation, preferably within Oncology and/or BioPharmaceuticals therapeutic areas.
- Demonstrated experience leading biomarker strategies within complex matrix organizations and driving cross-functional alignment across scientific, clinical, data science, pathology, diagnostic, and program teams.
- Strong expertise in computational pathology, digital pathology, image analysis, and AI-enabled biomarker development, including experience applying quantitative methods to histopathology data to address translational and clinical questions.
- Solid understanding of disease biology and pathophysiology relevant to Oncology and/or BioPharmaceuticals, including mechanisms of response and resistance, tissue biology, microenvironment interactions, and disease progression.
- Experience integrating diverse data modalities, including tissue-based biomarkers, imaging data, molecular profiling, blood-based biomarkers, and clinical data, to generate biological and translational insights.
- Strong analytical and quantitative skills, including experience interpreting complex multidimensional datasets and connecting computational findings to biological hypotheses, clinical outcomes, and drug development decisions.
- Working knowledge of AI and machine learning methodologies applicable to biomarker discovery, including supervised learning, foundation models, multimodal approaches, and emerging AI technologies.
- Understanding of biomarker development pathways, clinical trial design, and translational research strategies across different stages of drug development.
- Strong communication, presentation, and influencing skills, with the ability to effectively engage scientific and clinical stakeholders and communicate complex concepts to diverse audiences.
- Demonstrated ability to balance scientific innovation with pragmatic execution, delivering high-quality outputs in a fast-paced drug development environment.
Desirable
- Experience supporting companion diagnostic development, analytical validation, clinical validation, regulatory submissions, or interactions with regulatory agencies.
- Experience developing quantitative biomarker strategies for patient stratification, trial enrichment, treatment response assessment, or translational decision-making.
- Hands-on experience with computational pathology workflows and programming languages such as Python or R.
- Strong publication record in computational pathology, translational medicine, biomarker science, AI, or related disciplines, with evidence of scientific leadership through conference presentations and external engagement.
- Experience collaborating with academic institutions, technology providers, CROs, diagnostic partners, and external scientific organizations.
- Familiarity with regulatory, ethical, and governance considerations related to AI-enabled biomarker development and healthcare 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
03-Aug.-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.
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