3rd Summer School Al4Imaging

The Summer School is organized by Universtitätsklinik für Radiologie und Nuklearmedizin and the Comprehensive Center for Artificial Intelligence in Medicine. 

The Summer School aims to support young scientists after their PhD in developing independent research ideas and preparing competitive proposals for third-party funding (e.g., DFG, FWF, or similar funding schemes). A central goal of the program is to strengthen collaboration between medicine and computer science in the rapidly evolving field of AI-driven imaging.

List of Speakers

• Ulrike Attenberger 
  Department of Biomedical Imaging and Image-Guided Therapy, MedUni Vienna/University Hospital Vienna, Austria 
• Paola Clauser 
  Department of Biomedical Imaging and  Image-Guided Therapy, Division of General and Paediatric Radiology, MedUni Vienna/University Hospital Vienna, Austria
• Mirjam Gehrwing
  University Institute for Diagnostic and Interventional Radiology, Klinikum Lippe, Germany
• Ben Glocker
  Department Infrastructure, Machine Learning for Imaging, Kheiron/RAEng Research, Chair in Safe Deployment of Medical Imaging AI, Department of Computing, Imperial College London, UK
• Horst Hahn
  Digital Medicine, University of Bremen, Fraunhofer MEVIS, Germany
• Anja Hennemuth
  Institute of Cardiovascular Computational Medicine, Charité - Universitätsmedizin Berlin; Fraunhofer Institute for Digital Medicine MEVIS, Bremen; Faculty of Computer Science and Electrical Engineering, Technical University Berlin, Germany
• Gregor Kasprian
  Department of Biomedical Imaging and Image-Guided Therapy, Division of Neuroradiology and Musculoskeletal Radiology, MedUni Vienna/ University Hospital Vienna, Austria
• Georg Langs
  Department of Biomedical Imaging and Image-Guided Therapy, MedUni Vienna/University Hospital Vienna, Comprehensive Center for Artificial Inelligence in Medicine, MedUni Vienna, Austria 
• Björn Menze
  Biomedical Image Analysis and Machine Learning, University of Zurich, Switzerland
• Chris van Run
  Grand Challenge, Diagnostic Image Analysis Group, Radboudumc, The Netherland
• Daniel Pinto dos Santos
  University Medical Center Mainz, Division for AI and Medical Imaging Data Science, Germany
• Veronika Schöpf
  Interdisciplinary Transformation University, Linz, Austria
• Laura Stappert
  Deutsche Forschungsgemeinschaft, Bonn, Germany
• Martin-Michael Uggowitzer
  Institute for Radiology and Nuclear Medicine, Central X-Ray Institute, LKH Hochsteiermark, Austrian Radiology Society, Leoben, Austria
• Gerling Widmann
  Department of Radiology, Tirol Kliniken GmbH, Medical University Innsbruck, Austria
• Song Xue
  Department of Biomedical Imaging and Image-Guided Therapy, Division of Nuclear Medicine, MedUni Vienna/University Hospital Vienna, Austria

Scientific Focus

Artificial intelligence (AI) is playing an increasingly important role in modern medicine. Advances in imaging technologies and data science enable new approaches for the analysis and integration of complex biomedical datasets.

Topics addressed during the Summer School include:

• automated disease detection and characterization
• radiomics and quantitative imaging analysis
• multimodal data integration
• integration of imaging and text data
• dose optimization
• structured reporting
• Large Language Models & Vision Language Models in Medicine

The Summer School provides a transdisciplinary training platform for researchers from medicine, computer science, engineering, and related natural sciences. Participants will work on developing and refining their own research ideas, with the aim of transforming them into competitive project proposals.

Who Should Apply

The Summer School is intended for early-career researchers after their PhD, with a background in medicine, natural sciences, computer science, or engineering, who are aiming to establish their independent research group.

Eligibility criteria

• Natural sciences / computer science / engineering: PhD recently completed or expected by the end of 2026
• Medicine: PhD or Dr. med. completed within the last five years prior to the application deadline
• At least one accepted scientific abstract or first-author publication
• No prior acquisition of major individual funding (e.g., DFG, FWF, or comparable programs)
• Interest in pursuing an academic career

The call is primarily directed (but not limited) at applicants who are actively involved in a relevant research group and who have not yet completed a habilitation or an equivalent qualification.

Application Documents

Applications must be submitted as a single PDF file and include:

• Curriculum vitae (max. 2 pages)
• List of publications and presentations
• Project outline (max. 4 pages)

The project outline should describe the background, research question, methodology, and scientific relevance of the proposed project. A detailed work plan or budget is not required.

Applicants must also provide confirmation from the head of their department that the following costs will be covered:

• Registration fee: € 850
• Travel and accommodation expenses

Participants are expected to bring their own laptop. Prior to the Summer School, guidance will be provided regarding technical preparation and software setup.

Program

The Summer School comprises a one-week program including lectures, interactive discussions, and practical sessions. A central component of the program is a collaborative hackathon, during which participants jointly develop a prototype AI-based imaging application.

Following the Summer School, participants will be encouraged to further develop their project outlines into competitive proposals for individual research funding (e.g., DFG, FWF, or European funding programs).

Application and Deadlines

• Application deadline: April 27, 2026
• Submission via ÖRG
• Number of participants: up to 36

Applicants will be informed about the outcome of the selection process via email on June 30, 2026.