PhD Position in Explainable AI for Dermatological Clinical Decision Support

• Curate large-scale dermatological image collections for visual representation learning addressing issues of data quality, diversity, and clinical relevance
• Interpret clinical concepts with visual representations
• Develop XAI decision support systems
• Design and conduct multi-centric clinical evaluations

• A Master's degree in Computer Science, Biomedical Engineering, or a closely related field, with excellent academic credentials
• Strong background in machine learning and computer vision. Previous experience with XAI, self-supervised learning, multimodal models, diffusion models, or hyperbolic learning is an advantage
• Experience working with medical data and/or healthcare projects is highly desired. Previous exposure to dermatology or other clinical fields is a plus
• Advanced programming skills, including experience in writing efficient and clean code, and familiarity with modern AI frameworks
• Ability to handle complex datasets, from preprocessing to model training and evaluation
• Excellent communication and collaboration skills. Willingness to work in an interdisciplinary team, interacting with clinicians, and fellow researchers
• Proficiency in English (oral and written); knowledge of other languages, in particular German, is an asset

• An opportunity to pursue a PhD in a cutting-edge, multidisciplinary research environment
• Close collaboration with clinical and research partners in dermatology and AI
• Flexible working conditions with a focus on achieving research excellence and personal growth
• Participation in conferences, workshops, and seminars
• A supportive environment that focus on publications in top-tier journals and conferences, and the transfer of knowledge to clinical practice

The largest educational institution of the six Central Swiss cantons, the Lucerne University of Applied Sciences and Arts offers state-of-the-art jobs and programmes. We share knowledge in Switzerland and abroad, we are forward-looking, creative, and committed to interdisciplinarity. Help us to shape and become a part of our shared, sustainable future.