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F眉r ein Forschungsprojekt zur Modellierung von Bildverarbeitungsmechanismen mittels neuronaler Netze suchen wir eine motivierte HK zur Mitarbeit in einem interdisziplin盲r arbeitenden wissenschaftlichen Team. Der Kandidat oder die Kandidatin sollte Vorkenntnisse aus dem Bereich Computer Vision sowie maschinelles Lernen bzw. Lernen in tiefen neuronalen Netzen mitbringen. Die Aufgabe besteht in der aktiven Mitarbeit bei der Entwicklung und Implementierung von L枚sungsans盲tzen der automatisierten visuellen Suche zur Detektion von Strukturen in Bildern.
Bei Interesse, bitte ein aktuelles Transcript of Records (TOR) an heiko.neumann@uni-ulm.de senden
1x PhD Position (TV枚D E13) in Neuro-Symbolic AI
University of Ulm
Institute of Neural Information Processing
Faculty of Engineering, Computer Science and Psychology
Within the KEMAI Research Training Group (https://kemai.uni-ulm.de/), a doctoral position (E13, 100%) is being advertised with the topic "Neuro-Symbolic Reasoning for Medical Imaging." Project description: This project investigates reasoning-based approaches to medical image interpretation, using cancer staging from PET/CT as primary application domain. It addresses two complementary aspects. First, modularization: rather than learning the full mapping from images to clinical decisions end-to-end, we decompose the problem into individually learnable cause-effect pairs and compose them through explicit reasoning at inference time, exploring this as a strategy for generalization when the combinatorial space of possible cases far exceeds available training data. Second, explanation: we investigate how structured reasoning processes can generate not just predictions but candidate hypotheses with supporting and opposing evidence, serving as a reasoning scaffold that makes the system鈥檚 logic transparent and useful to clinicians. The project sits at the intersection of neuro-symbolic AI, medical imaging, and clinical decision support, with the broader aim of understanding where the boundary between learning and reasoning should lie in medical AI systems.
The University of Ulm is an equal opportunity employer: Handicapped individuals are strongly encouraged to apply, and so are women in areas in which they are underrepresented.
Candidates should send a CV and a brief statement of interest to
Prof. Dr. Dr. Daniel Alexander Braun daniel.braun@uni-ulm.de
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Prof. Dr. Dr. Daniel Alexander Braun
Institute of Neural Information Processing
Faculty of Engineering, Computer Science and Psychology
Ulm University
James-Franck-Ring
D-89081 Ulm
Germany
phone: +49 (0)731 50 - 24150
fax: +49 (0)731 50 - 24156
email: daniel.braun@uni-ulm.de