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Senior Scientist, AI Pathologist (w/f/d) (FTC, Maternity Cover)

AstraZeneca

·

3 days ago

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Location
AZ Computational Pathology GmbH - Munich, Germany
Type
Full-time
Department
Education
Seniority
Senior
Source
Workday

Description

About AstraZeneca

AstraZeneca is a global, science-led, patient-focused biopharmaceutical company that focuses on the discovery, development and commercialization 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

Welcome to Computational Pathology Munich, one of over 400 sites here at AstraZeneca, providing a collaborative environment where everyone can feel comfortable to be themselves - a value that is at the core of AstraZeneca's priorities. To help you maintain your best self, here's a sneak peek into some of the things we provide: after-work events, lunch & learns, a spacious and sustainable office working environment, events, family and childcare support and of course the Alps around the corner for hiking, biking and skiing.


We are looking for an experienced

 

Senior Scientist, AI Pathologist (w/f/d)

 

to join AstraZeneca on a fixed-term maternity cover.

 

In this role, you will bring your pathology expertise to the development of AI-powered computational pathology and biomarker solutions. Working at the intersection of pathology, biomarker science and data science, you will help turn complex biological and clinical questions into meaningful insights from human tissue and image data.

You will work closely with colleagues across Translational Medicine, Biomarkers, Data Science, Engineering and Quality, as well as external diagnostic and technology partners.

 

As Senior Scientist, AI Pathologist (w/f/d), you will provide pathology expertise across computational pathology and AI-enabled biomarker projects.

You will help ensure that the tissue and image data used to develop AI solutions are scientifically robust, biologically meaningful and clinically relevant, from biomarker discovery and dataset design through annotation, model evaluation and interpretation.

 

Key Responsibilities

  • Provide pathology expertise for AI and biomarker projects, translating disease biology, tissue morphology and diagnostic criteria into requirements for datasets, annotations and model evaluation.
  • Support biomarker discovery and study design, including tissue and image requirements, cohort and sample selection, staining characteristics and relevant pathology subgroups.
  • Develop and review annotation and ground-truth strategies for AI model development, including annotation criteria and pathology review of annotated datasets.
  • Evaluate AI model performance from a pathology perspective, identifying relevant patterns, potential failure modes and limitations across tissues, morphology, staining and patient subgroups.
  • Ensure pathology and image-analysis quality, including the biological and clinical interpretation and explainability of model outputs.
  • Interpret and communicate findings, translating complex pathology and AI results into clear scientific conclusions and recommendations.
  • Collaborate across disciplines and with external partners, including Translational Medicine, Biomarkers, Data Science, Engineering, Quality, diagnostic and annotation partners.
  • Contribute to high-quality, traceable ways of working, supporting appropriate documentation, quality standards and continuous improvement across computational pathology projects.

 

Your Profile

You are an experienced pathologist with a strong interest in digital and computational pathology, AI-enabled biomarker development and oncology research, and enjoy working at the intersection of pathology, data science and translational medicine.


Essential qualifications and experience:

  • Medical degree with formal training and board certification in anatomic/anatomical pathology, or an equivalent recognised qualification, with strong expertise in oncology, histopathology and immunohistochemistry (IHC). A veterinary degree may also be considered for candidates with highly relevant experience in human tissue and disease biology.
  • Hands-on experience reviewing human tissue and whole-slide images, interpreting IHC and applying pathology expertise in research, biomarker development, dataset design or annotation.
  • Experience with, or strong exposure to, digital/computational pathology, AI or image-analysis workflows, including the evaluation and interpretation of model outputs.
  • Strong scientific communication and collaboration skills, with experience working in global, cross-functional teams across scientific and technical disciplines.

Desirable:

  • Experience with quantitative image analysis and advanced or multiplex imaging, such as multiplex immunofluorescence or multiplex IHC.
  • Familiarity with GxP-aligned quality requirements, SOP-driven workflows and pathology/image-analysis quality control.
  • Experience collaborating with external annotation, diagnostic, tissue or technology partners.

 

What you can expect:

  • The opportunity to shape business and portfolio strategies within a global, science-led biopharmaceutical organization.
  • Collaboration with senior leaders, cross-functional experts and external stakeholders.
  • An environment that encourages knowledge sharing, continuous development and strategic thinking.
  • The opportunity to contribute your expertise to important portfolio and business decisions across AstraZeneca.

 

Date Posted

06-Nov.-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.

Skills

Data Science

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