Researcher in Digital Pathology and Federated Learning (with or without PhD)

Position title: Researcher / Junior Researcher (with or without PhD)

Workload: Full-time

Position Description

We are seeking a motivated researcher to join our team working on Federated Learning (FL), Digital Pathology, whole-slide image (WSI) analysis, and AI in healthcare. The position is suitable for applicants with a PhD or those who have not yet completed one. You will have the opportunity to work with state-of-the-art technologies and contribute to solving real clinical challenges such as multi-institutional collaboration, privacy-preserving analytics, and AI model generalizability.

Key Responsibilities

Conduct research in Federated Learning for digital pathology (WSI segmentation, classification, feature extraction, etc.).

Develop and optimize deep learning models using gigapixel histopathology images.

Participate in federated model training, privacy-preserving methodologies, and approaches for handling non-IID clinical data.

Prepare scientific publications, technical reports, protocols, and conference presentations.

Collaborate with international project partners, hospitals, and research consortia.

Required Qualifications

Higher education degree in data science, biomedical sciences, computer science, engineering, or a related field.

PhD degree is an advantage, but not required.

Experience with Python and deep learning frameworks (PyTorch and/or TensorFlow).

Familiarity with digital pathology, WSI processing, or AI in medicine is a strong asset.

Good command of English (scientific and professional communication).

We Offer

3300 EUR gross monthly salary (full-time) for the PhD holders.

Participation in high-level international research projects.

Opportunities for scientific publications and academic career development.

Flexible working hours and options for partial remote work.

A modern research environment with access to compute infrastructure and GPU resources.

How to Apply

Please submit the following documents:

CV

Motivation letter

(If available) List of publications or portfolio