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costs and energy requirements of state-of-the-art deep learning models significantly, while democratizing them for a vast community of users, researchers, and practitioners. The task is to perform just
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We are looking for a highly motivated PhD candidate interested in AI-based methods, including machine learning and language technologies, for the integration and analysis of clinical, advanced data
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The University of Luxembourg invites applications for a fully funded Ph.D. position in machine-learning force fields (MLFFs), uncertainty quantification, and atomistic simulations within the FNR
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, Reasoning and Validation (Serval) research group and work on a research project related to the application of machine learning for official statistics. The subject of the thesis will be “Exploring Large
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within the project AI4TECS Writing a doctoral dissertation in computer science Publishing research findings in leading international conferences and high‑impact journals in AI, machine learning, and
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-FNR PEARL Research Grant in the area of Information Systems Engineering, and, depending on interest, in fields, such as Generative AI & Machine Learning, Data Privacy, Cyber Security, Digital Identities
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understand, explain and advance society and environment we live in. Your role The University of Luxembourg invites applications for a fully funded Ph.D. position in machine-learning force fields (MLFFs
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· An environment encouraging curiosity, innovation and entrepreneurship in all areas · Personalized learning programme to foster our staff’s soft and technical skills · Multicultural and international
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SD-26045-RESEARCHER IN ADVANCED PLASMA-ASSISTED DEPOSITION PROCESS DEVELOPMENT FOR CATALYTIC THIN...
characterisation. Timely and high-quality contributions to project deliverables, reports, and milestones, including scientific publications. Team-oriented attitude, continuous learning mindset, strong documentation
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if they demonstrate strong relevant skills. Coursework or strong background in computational mechanics / FEM, numerical methods, and scientific programming. Exposure to machine learning / data-driven modelling and/or