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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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language models) against various threats that may occur in the real-world. Successful PhD candidates will extensively explore and develop software security and testing techniques for machine learning systems
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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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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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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 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
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I-2503 – PHD IN EXPLAINABLE AI FOR DATA-DRIVEN PHYSIOLOGICAL AND BEHAVIORAL MODELLING OF CAR DRIVERS
Master’s degree or Engineer diploma in Computer Science, Artificial Intelligence, Data Science, Machine Learning, or a related field. Experience and skills · Strong knowledge of AI, Machine Learning
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described below? Are you our future colleague? Apply now! Education · A PhD in machine learning, AI, with a focus on application of AI on energy systems. Experience and skills · Strong
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application of machine learning algorithms to automatically classify freshwater benthic diatoms at the species level and quantify key morphological traits. These advancements aim to improve ecological