65 machine-learning-"https:" "https:" "https:" "https:" "https:" "University of St" "St" PhD positions at Technical University of Munich
Sort by
Refine Your Search
-
subjects, high interdisciplinary desire to learn, and willingness to cooperate, openness for internationalization and diversity, very good verbal and written English communication skills (good command
-
biological techniques (SSR, GC-EAD, EAG). •Experience in analytical chemistry (GC-FID, GC-MS). •Experience in or willingness to learn statistical data analyses, data processing and analytical chemical analyses
-
, development, and evaluation of Machine Learning and Deep Learning methods Prototype development Literature review Publication and presentation of scientific results in international conferences and related
-
, designed for acidic water-splitting reactions in polymer electrolyte membrane (PEM) units (e.g., https://onlinelibrary.wiley.com/doi/full/10.1002/aenm.202301450). Your tasks in detail: Collaborate closely
-
for Preventing Stomach Cancer 18.03.2026 The order of the quantum world 18.03.2026 150 Years of Electrical and Computer Engineering at TUM RSS Todays events no events today. Calendar of events Find more topics on
-
and evaluation of human-machine interactions as well as the design of complex socio-technical systems. The Automated Driving Research Group addresses topics related to the interaction between users and
-
12.01.2026, Academic staff The Professorship of Machine Learning at the Department of Computer Engineering at TUM has an open position for a doctoral researcher (TV-L E13 100%; initial contract 1.5
-
and written English and the will to acquire a certain working language of German. What we offer We offer The Chair Group of Production and Resource Economics offers a highly international and
-
, leveraging a principled combination of passivity-based control methods, machine learning, and human-in-the-loop systems to enable robust teleoperation in uncertain and delayed communication environments. Key
-
focus is developing and characterizing metallic high-performance materials for/through additive technologies using experiments and computer-aided methods. Furthermore, the chair is dedicated