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related discipline • Some knowledge of the theory of materials and experience with computational methods in materials science • Some experience with machine-learning interatomic potentials • Good
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learning, etc.); · Knowledge of explainable AI and Knowledge Graphs with ontology (e.g., RDFS, OWL); · Demonstrated experience with common advanced signal processing techniques (e.g. denoising
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SD- 26053 PHD IN ULTRA-FAST MACHINE-LEARNING INTERATOMIC POTENTIALS FOR NANOINDENTATION OF TIC MA...
materials science or a related discipline • Some knowledge of the theory of materials and experience with computational methods in materials science • Some experience with machine-learning interatomic
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should have strong digital signal processing and mathematical backgrounds evidenced by grades and/or prior publications. Additionally, the candidate should have expertise or strong interest (evidenced by
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group with broad research competences and interests, with expertise covering mathematics, engineering, computer science and social sciences. We offer excellent working conditions in an international and
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and advancing techniques such as machine learning, graph-based network analysis, and synthetic data generation, the project tackles key challenges in anomaly detection, transaction classification, and
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one-fits-all model was proven unsuccessful. Large Language Models (LLMs) and knowledge graph models are expected to harmonize the formats and semantics but there are many open questions about their
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. Our research brings together social theory, empirical studies guided by a range of interpretive methodologies, and the critique as well as advancement of interventions and social policies. We
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interdisciplinary character. The Faculty of Science, Technology and Medicine (FSTM) at the University of Luxembourg contributes multidisciplinary expertise in the fields of Mathematics, Physics, Engineering
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character. The Faculty of Science, Technology and Medicine (FSTM) at the University of Luxembourg contributes multidisciplinary expertise in the fields of Mathematics, Physics, Engineering, Computer