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The Luxembourg Institute of Socio-Economic Research (LISER) is recruiting aPhD Candidate in Geospatial Data Science and Environment with a focus on Artificial Intelligence and Machine Learning (f/m
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at tunable temperature and photopolymerization of the precursor. The practical work will be complemented by fluid mechanics computer simulations, including solutions employing machine learning, and theoretical
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proof-of-concept software tools Machine learning is a plus Strong analytical and programming skills are required (Python, Matlab, and C/C++). Prior proven experience in data-driven innovation projects is
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use tools such as artificial intelligence/machine learning, graph theory and graph-signal processing, and convex/non-convex optimization. Furthermore, our activities are experimentally driven and
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of the candidate include (but are not limited to): · Uncertainty quantification · Regularization techniques · Machine learning · deep learning · High‐dimensional statistics · Dimensionality reduction · Causal
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variants of the sodium channel Nav1.1, which are associated with different forms of epileptic syndromes and migraine. The aim of the project is to use machine-learning assisted molecular dynamics simulations
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We are looking for a doctoral candidate with a strong computational, engineering, data scientific or machine learning background that is keen to work in an interdisciplinary environment and open to
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Pneumatic Tires, Structure-Process-Properties Relationships. How will you contribute? Do you have proven skills in data analysis, machine learning, as well as in mathematical and computational modelling? You
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be found on hpc.uni.lu . The activities include classical HPC applications, such as simulation and modeling, as well as artificial intelligence and machine learning, which bridge computational science
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We are seeking a highly motivated PhD candidate with a strong interest or background in AI as well as in one or more of the following areas: Generative AI, Natural Language Processing, Deep learning