49 parallel-and-distributed-computing PhD positions at Technical University of Munich
Sort by
Refine Your Search
-
societal aspects (ELSA) of NeuroAI in the life sciences and biomedicine. The project focuses on (i) neu-romorphic computing inspired by the human brain and (ii) AI-enabled neurotechnologies for clinical and
-
Technical University of Munich School of Computation, Information and Technology Chair of Theoretical Information Technology Theresienstrasse 90, 80333 Munich https://www.ce.cit.tum.de/en/lti/team/boche
-
fashion. Research topics include, but not limited to, i) handling distributed DL models with data heterogeneity including non i.i.d, and domain shifts, ii) developing explainability and quality control
-
fashion. Research topics include, but not limited to, i) handling distributed DL models with data heterogeneity including non i.i.d, and domain shifts, ii) developing explainability and quality control
-
tailored computational methods are needed. This project aims at combining probabilistic machine learning methods with prior knowledge in the form of graphs to analyze and predict food-effector systems. Key
-
molecular level. To yield new insights into food-effector systems, sophisticated and tailored computational methods are needed. This project aims at leveraging graph-theoretic approaches to analyze and
-
extensive server infrastructure for research Excellent training and career support opportunities (courses, personal coaching, ...) Your qualifications Master’s degree in Computer Science, Computational
-
infrastructure for research Excellent training and career support opportunities (courses, personal coaching, ...) Your qualifications Master’s degree in Computer Science or a similar field Good theoretical
-
Chair of Biological Imaging 02.02.2026, Academic staff We are looking for a candidate (m/f/x) who will use the combination of our spectroscopy infrastructure, and structural information of the proteins to advance the photophysical research on (photoswitching) proteins developed in the...
-
use of machine learning methods to process complex data sets. The focus is on techniques such as ultrasound, radar, computed tomography, acoustic emission analysis, and infrared thermography. Industry