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

Robert-Bosch-Krankenhaus GmbH; Stuttgart; Vor Ort; EUR 50.000 - 80.000; Vollzeit

Zusammenfassung

An innovative research institute is seeking a Post-Doc in Artificial Intelligence for Breast Cancer Image Analysis. This exciting role involves analyzing large-scale histopathology datasets and developing advanced machine learning models to enhance clinical cancer research. Collaborating with national and international biomedical partners, you will leverage your expertise in AI-driven image analysis to predict breast cancer subtypes and treatment responses. Join a dynamic and interdisciplinary team, and contribute to groundbreaking research that aims to transform cancer diagnostics and treatment. This is a unique opportunity to work at the forefront of computational pathology and make a significant impact in the field.

Leistungen

Access to state-of-the-art computational resources

Opportunities for publication in top-tier journals

International research collaborations

Dynamic and collaborative environment

Qualifikationen

• PhD in bioinformatics with expertise in AI and data science.
• Strong background in AI-driven image analysis and Python programming.

Aufgaben

• Analyze histopathology datasets and develop machine learning models.
• Predict breast cancer subtypes and treatment response using image analysis.

Kenntnisse

Python Programming

AI-driven Image Analysis

Deep Learning (PyTorch, TensorFlow)

Communication Skills

Interdisciplinary Research

Ausbildung

PhD or equivalent in Bioinformatics

Tools

Unix/Linux Systems

Jobbeschreibung

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

Full-time

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

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 :
• Phone :

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.