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: https://www.hds-lee.de/admission/openpositions/ Your Profile Mandatory qualifications are: M. Sc. degree in meteorology, physics, mathematics, or a related field Good knowledge in data handling and
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below and above its Néel temperature. The goal is to disentangle magnetic and structural contributions to electron diffraction data and to compare the results with measurements recorded using X-rays and
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, robustness, and fairness of LLM-based research indicators. The main use case for assessing the quality of publications is to improve the reliability of literature-derived data in our technology database
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requires an unprecedented computing and storage infrastructure. Processing these enormous amounts of data in a future data center, however, consumes significant resources. The fundamental challenge is: How
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drought Motivation for modelling and data analysis Programming experience or willingness to develop it Good English communication skills (at least B2 level according to the CEFR: https://go.fzj.de
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and interpretation of experimental data Your Profile You are studying physics, material sciences, engineering, or a related subject at a university and are looking for a topic for a master's thesis
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prediction. In this thesis, you will focus on the quantification of model uncertainty, that arises from limited knowledge and the quantification of data uncertainty, that arises from data-inherent
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must be inferred from models that are incomplete and data that involve errors. For such challenges, Bayesian analysis using Markov Chain Monte Carlo (MCMC) has become the gold standard. For addressing
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embedded FPGA-based intelligence near seismic sensor arrays, you will explore methods to maximize prediction performance while minimizing data transmission and latency. Your key tasks include: Evaluating
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surrogate models and experimental data from a pilot-scale settler are available. The project offers close supervision from doctoral researchers in machine learning and process control. Your Profile