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such as the NEPS. Potential research areas include (but are not limited to): Item response modeling of achievement tests Analysis of process data (e.g., response times) to enhance competence measurements
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– from the modeling of material behavior to the development of the material to the finished component. PhD Position in Machine Learning and Computer Simulation Reference code: 50145735_2 – 2025/WD 1
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phenomena such as the spread of misinformation or the formation of filter bubbles. For this, we rely on rigorous probabilistic methods to model and analyse the intrinsic complexities of these systems
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16.08.2023, Wissenschaftliches Personal The Chair of Computational Modeling and Simulation (CMS) at the Technical University of Munich invites applications for the position of a Research Assistant
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modelling • A high fascination for technical/scientific problems of theoretical and numerical research • Experience in the field of numerical time-accurate flow simulation, preferably turbomachinery • Ability
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to model and analyse the intrinsic complexities of these systems. This research direction requires advancements in modern probabilistic tools, including spatial random graphs, random walks, and Markov chains
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to probe metabolic states and function of control mechanisms. Analysis of strain performance and control mechanisms using computational tools (e.g., flux balance analysis, kinetic models, network component
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) in the field of spatial equilibrium modeling, starting on 01.11.2025. PhD positions are funded for 3 years with a 75% share of the total E13 salary in accordance with the German public tariff scheme
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Description Are you interested in developing novel scientific machine learning models for a special class of ordinary and differential algebraic equations? We are currently looking for a PhD
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civil/electrical/control engineering or mathematics or related study programs with a solid basis in choice modelling and/or reinforcement learning, with knowledge of MATSim is advantageous. Description