12 computational-modelling-"https:" Postdoctoral positions at Technical University of Munich
Sort by
Refine Your Search
-
Category
-
Field
-
/11250664 https://www.jmlr.org/papers/v26/25-1161.html Job Specifications For PhD applicants: Excellent Master’s degree (or equivalent) in engineering, computer science, or related disciplines (typically
-
Master’s theses Requirements: Master’s or PhD degree with above-average results in Applied Maths (analysis, numerics, modeling) or in a comparable program with a strong math. focus and knowledge in
-
04.02.2026, Academic staff The successful candidates will be part of the Munich Climate Center and the Earth System Modelling group at TUM (https://www.asg.ed.tum.de/esm/home/) and will be closely
-
of stem-cell derived models, these platforms open new avenues to systematically explore tissue self-organization and disease mechanisms. The group of Prof. Bausch is establishing an automated cell culture
-
-XRF, Raman, FTIR in reflection mode) to enable multimodal data fusion and automated material characterization. • Apply and further develop machine-learning and statistical models (e.g. PCA, SAM
-
Models, LLMs, etc. PhD and PostDoc Positions in Visual Computing & AI The Visual Computing & Artificial Intelligence Group at the Technical University of Munich is looking for highly motivated PhD students
-
22.03.2021, Academic staff The 3D AI Lab at the Technical University of Munich is looking for highly motivated PhD students and PostDocs at the intersection of computer vision, machine learning, and
-
learning is also appreciated. PhD: The candidate is expected to have some background in theoretical computer science, including some of the following areas: automata, logic, games, verification/model
-
are modeled using information theory. We wish to investigate how interleaving can reduce the overhead and computational load due to coding coefficients required in classical linear random network coding
-
PhD/Postdoc position in trustworthy data-driven control and networked AI for rehabilitation robotics
of such systems, taking particularly into account model uncertainties as well as limitations pertaining to acquisition of data, communication, and computation. We apply our methods mainly to human-robot-teams