40 machine-learning-"https:" "https:" "https:" "https:" "https:" "https:" "Simons Foundation" Postdoctoral positions at Technical University of Munich in Germany
Sort by
Refine Your Search
-
, interns, and PostDocs at the intersection of computer vision and machine learning. The positions are fully-funded with payments and benefits according to German public service positions (TV-L E13, 100
-
multimodal vision-language models for prompt-based 3D medical image segmentation Work with large-scale clinical CT datasets and scalable deep learning pipelines Validate models in close collaboration with
-
: - QUANTITATIVE VERIFICATION: analysis of probabilistic systems (Markov decision processes, stochastic games, chemical reaction networks), automata theory and temporal logic, machine learning in verification
-
Informationen zur Stelle: https://www.pisa.tum.de/pisa/jobs/ Für eine der PISA Hauptdomänen (Lesen, Mathematik, Naturwissenschaften) nach Wahl wird zum nächstmöglichen Zeitpunkt ein*e Postdoc gesucht. Nähere
-
is expected. Background Information: Nat. Chem. 2015, 7, 105; Chem. Eur. J. 2019, 25, 4590; Angew. Chem. Int. Ed. 2019, 58, 418; Nanoscale 2021, 13, 19884. www.sengegroup.eu https://www.ias.tum.de
-
of computer vision and machine learning. The positions are fully-funded with payments and benefits according to German public service positions (TV-L E13, 100% for PhDs and TV-L E14, 100% for PostDocs; 45k
-
PhD/Postdoc position in trustworthy data-driven control and networked AI for rehabilitation robotics
learning • robotics and/or mechatronics • computer languages C, C++ and Python and interest to work in an interdisciplinary environment are desired. German language skills are necessary for this position
-
to joint research activities, publications, and surveys. Requirements PhD degree (or near completion) in robotics, control, machine learning, or a related field; Strong publication record demonstrating
-
, imaging). • Solid foundations in signal processing and statistics. • Experience with machine learning for regression (e.g., tree-based methods, neural networks) • Hands-on experimental skills: ability and
-
training machine learning models (ideally with a focus on LLM), high-performance computing, data management, and software architecture Strong Python programming skills and familiarity with machine learning