Post-Doc in Artificial Intelligence for Breast Cancer Image Analysis (m/f/d)

Post-Doc in Artificial Intelligence for Breast Cancer Image Analysis (m/f/d) Full-time Tätigkeitsfeld: Wissenschaft und Forschung Beschäftigungsumfang: Vollzeit Company Description The Dr. Margarete Fischer-Bosch Institute of Clinical Pharmacology, Stuttgart (Director: Prof. Dr. M. Schwab) is operated by the Robert Bosch Foundation. Since its foundation in 1973, the institute has emerged as Germany's largest and most renowned scientific research unit in the field of clinical pharmacology. Main research activities concentrate on the influence of genetic, epigenetic, metabolic and non-genetic factors on variability of drug efficacy and their contributions to disease development. Job Description The project involves analyzing large-scale histopathology datasets from breast cancer tissue and developing machine learning models for image-based biomarker discovery. This position offers a unique opportunity to work at the intersection of computational pathology, artificial intelligence (AI), and oncology, contributing to clinical cancer research through advanced computer vision applied to exclusive image datasets. We aim to use cancer cell morphology and nuclear features in tissue slides to predict breast cancer (molecular) subtypes, prognosis and treatment response. This work is carried out in close collaboration with our outstanding national and international biomedical partners. Qualifications The ideal candidate will have a PhD or equivalent in bioinformatics, with expertise in various methods of artificial intelligence and data science. A strong background in AI-driven image analysis, proficiency in Python programming including deep learning frameworks such as PyTorch and TensorFlow, and a solid publication record are required. Additional desirable qualifications include: Experience in working with whole-slide images in histopathology Proficiency in working with Unix/Linux Systems Excellent communication skills and fluency in English Interest in interdisciplinary research Knowledge of cancer biology Additional Information We offer: A dynamic and collaborative environment focused on the clinical application of new biological insights Access to state-of-the-art computational resources and unique, high-quality histopathology datasets Opportunities to publish in top-tier journals and engage in international research collaborations A highly motivated interdisciplinary team The position is available immediately. Contact: Dr. Florian Büttner Phone: 0711/8101-2091 The Dr. Margarete Fischer-Bosch-Institute for Clinical Pharmacology seeks to raise the number of women in research and teaching and therefore urges qualified women academics to apply for these positions. Equally qualified applicants with disabilities will be given preference. Please submit your application including motivation letter, CV, certificates and contact details of two academic references. Sind Sie bereit für eine neue Herausforderung? Dann bewerben Sie sich jetzt über unser Online-Karriereportal . Die angegebenen Arbeitgeberleistungen können je nach Position und Anstellungsverhältnis variieren. Bitte beachten Sie die geltenden Nachweispflichten aufgrund des Infektionsschutzgesetzes als Einstellungsvoraussetzung. Wir schätzen die Einzigartigkeit und Unterschiedlichkeit unserer Mitarbeitenden und fördern ein Arbeitsumfeld, das unabhängig von Alter, Geschlecht, sexueller Identität, Behinderung, Herkunft oder Religion gleiche Chancen ermöglicht. Mit Einreichung Ihrer Bewerbungsunterlagen stimmen Sie zu, dass Ihre Bewerberdaten in der Bewerbermanagementsoftware SmartRecruiters aufgenommen und verarbeitet werden. Hinweise zu unserem Datenschutz finden Sie hier: Datenschutz . I'm interested I'm interested The project involves analyzing large-scale histopathology datasets from breast cancer tissue and developing machine learning models for image-based biomarker discovery. This position offers a unique opportunity to work at the intersection of computational pathology, artificial intelligence (AI), and oncology, contributing to clinical cancer research through advanced computer vision applied to exclusive image datasets. We aim to use cancer cell morphology and nuclear features in tissue slides to predict breast cancer (molecular) subtypes, prognosis and treatment response. This work is carried out in close collaboration with our outstanding national and international biomedical partners. The ideal candidate will have a PhD or equivalent in bioinformatics, with expertise in various methods of artificial intelligence and data science. A strong background in AI-driven image analysis, proficiency in Python programming including deep learning frameworks such as PyTorch and TensorFlow, and a solid publication record are required. Additional desirable qualifications include: Experience in working with whole-slide images in histopathology Proficiency in working with Unix/Linux Systems Excellent communication skills and fluency in English Interest in interdisciplinary research Knowledge of cancer biology