34 phd-agent-based-modelling Postdoctoral research jobs at Technical University of Munich in Germany
Sort by
Refine Your Search
-
cooperation with the other scientists is a prerequisite. Your profile: You have a PhD, work experience and several publications in the field of solid oxide cells. In addition, fluent written and spoken English
-
consortium-based tasks related to the 6G-Life project. Additionally, the methods and findings developed throughout the PhD track will be scalable and applicable to other research projects in MIRMI
-
01.07.2025, Wissenschaftliches Personal The position is based within the research group of Deniz Kus, Professor for Representation Theory at the Department of Mathematics, part of the TUM School
-
. The position is based within the research group of Deniz Kus, Professor for Representation Theory at the Department of Mathematics, part of the TUM School of Computation, Information and Technology (CIT
-
materials science • Extensive knowledge of computer-based modelling and simulation methods in materials science of metals, e. g. Calphad method, precipitation simulation, cellular automata, kinetic Monte
-
. Your qualifications An excellent PhD degree either in Computer Science, Physics, Mathematics or related fields, ideally with a background in quantum theory, quantum computing or quantum machine learning
-
to 5 and more years. Requirements: • You have a PhD degree (or postgraduate degree MSc) in a computational discipline, preferably with significant experience in Bioinformatics or Computational Biology
-
preliminary work! • You will characterize metalloid transport proteins. • You will be involved in the training of students on the Bachelor and Master level. YOUR QUALIFICATIONS AND SKILLS • You have a PhD or
-
communication system 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
-
on the design and evaluation of innovative data- and machine learning-based systems to integrate more renewable energy into our energy systems and make energy use more efficient. We develop new optimization