53 machine-learning "https:" "https:" "https:" "https:" "https:" "UCL" PhD scholarships at Technical University of Munich
Sort by
Refine Your Search
-
tools for distributed models, and iii) robustness to data and model poisoning attacks. In this context, we are looking for a PhD Candidate who has a strong background in machine/deep learning to push our
-
tools for distributed models, and iii) robustness to data and model poisoning attacks. In this context, we are looking for a PhD Candidate who has a strong background in machine/deep learning to push our
-
? Our current research is based in India, Rwanda, and Uganda, but we are always seeking ways to learn about and work in new places! You can find out more about us here. About the PhD Researcher Position
-
processing parameters. You will develop machine learning models to analyse experimental datasets and uncover structure-function relationships that determine membrane performance. By combining statistical
-
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
-
, 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
-
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
-
are available in early 2025 and will remain open until filled. Further information: https://www.mls.ls.tum.de/en/plasysbio/home/ Selected recent publications Graf, A., Bassukas, A.E.L., Xiao, Y., Barbosa, I.C.R
-
, 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
-
(https://soilsystems.net/ ), a Priority Programme (SPP 2322) funded by the Deutsche Forschungsgemeinschaft (DFG; German Research Foundation). Within SoilSystems, scientists from different disciplines from