PhD Position in Neuro-Symbolic AI at Ulm University
1x PhD Position (TVöD E13) in Neuro-Symbolic AI University of Ulm Institute of Neural Information Processing Faculty of Engineering, Computer Science and Psychology There is a fully funded PhD position available at the Institute of Neural Information Processing, Ulm University. At the institute we are interested in the mathematical foundations of intelligent behaviour in biological and artificial systems. The PhD topic will revolve around the fundamental question of how the abstraction capabilities of classic symbolic knowledge systems can be combined with the sub-symbolic pattern recognition capabilities of neural networks in order to allow neural networks to take existing knowledge into account when making predictions. The PhD position will be part of the newly established DFG graduate school KEMAI (Knowledge Infusion and Extraction for Explainable Medical AI). The structured PhD programme has a duration of 3 years with the possibility of extending for one more year. The candidate will have the opportunity both to make contributions to fundamental questions in AI and cognitive science and to apply their work directly in the context of medical imaging through collaboration with University Clinic. Within the same broad topic area there is a second PhD position available at the Institute of Medical Systems Biology that includes investigation of genetic markers. The applicants should have a strong mathematical background, hold a degree in natural science, mathematics, economics, psychology, computer science, engineering or similar and have a keen interest in neuroscience and artificial intelligence. The University of Ulm is an equal opportunity employer. Candidates should send a CV and a brief statement of interest to Prof. Dr. Dr. Daniel Alexander Braun daniel.braun@uni-ulm.de
Hi everyone, We’re looking for 1 highly motivated PhD student (d/f/m). If you’re interested -or know someone that could be-, please send the CV, a motivation letter, and a recent transcript of records in PDF to Henrike.Heyne@hpi.de<mailto:Henrike.Heyne@hpi.de> The project * Topic: “Predicting epilepsy with clinical data from the Mount Sinai Health System” * Who: Co-supervised by 2 PIs, Henrike Heyne<https://scholar.google.com/citations?user=S0laek4AAAAJ&hl=en> (Potsdam, Germany) and Isotta Landi<https://profiles.mountsinai.org/isotta-landi> (New York City, USA) * Where: HPI at the Potsdam University, including a 1-year stay at the Mt. Sinai Hospital in NYC. * When: start date flexible but ideally ASAP. * Data: real-world structured and unstructured Electronic Health Records, which includes clinical notes, EEG data, and genomic data. * Methods: Disease prediction, deep learning (probably including LLM and image classification). * Funding: Project funded by the Hasso-Plattner Foundation for 3 years (extension possible), travel budget included. Applicants should have * A background in (bio-)informatics, life science, medicine, statistics or related field * Advanced programming skills are a plus (R/python, others) * Experience with genetic and clinical data are a plus * Ability to work independently and in a team * Commitment to an interdisciplinary and international research project * Excellent communication skills in English For any question, please reach out to Henrike.Heyne@hpi.de<mailto:Henrike.Heyne@hpi.de> Thanks, Andrea Eoli
participants (2)
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Daniel Braun
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Eoli, Andrea