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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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-Checking, Argument Mining, Automated Planning, and Decision-Making. Training, domain adaptation, and evaluation of cutting-edge LLMs and Multi-Modal models in the cloud and on premise. Software Engineering
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the project “Modeling Great Ape Signaling Behavior” under the auspices of the Collaborative Research Center “Common Ground” (CRC1718), which is funded by the German Research Foundation (DFG), at the University
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complementary methodologies (corpus data and offline experimental measures). On the theoretical side, the project will develop a formal compositional model that generates the observed parameters of variation and
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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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Researcher in Language Evolution / Probabilistic or Evolutionary Modeling / Primate Communication (m/f/d, E13 TV-L, 75%) The position will be filled for a fixed term until June 2029. Payment is at 75
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for climate-positive and CO2-negative processes. What you will do Optimization of the pilot plant for the combustion of solid fuels (biomass, waste) with oxygen and subsequent CO2 capture Development of models
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viability using multiple detection techniques (FACS, microscope, spectrophotometer). Collaboration on the analysis of created bacteria in Zebrafish models. Analyse data, contribute to scientific publications
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isotope ratio mass spectrometry (IRMS) and gas chromatography coupled with mass spectroscopy (GC-MS), as well as other spectrometric methods Experimental and modelling analysis of relevant processes in
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mechanisms occurring in these materials and their synthesis over all relevant length scales (e.g., cutting-edge ab initio methods, atomistic simulation methods, multi-scale modelling, machine learning) High