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supports to cover fees and basic expenses related to the PhD programme. PhD students at the department are embedded in the interdisciplinary context of the School of Social Sciences and Philosophy which also
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embedded in the Doctoral Programme in Complex Systems Science at the University of Luxembourg. The modelling approaches developed in this project share conceptual similarities with adaptive network and
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Department of Land Surveying and Geo-Informatics Research Assistant Professor in Space Science (Ref. 251211003) The Department of Land Surveying and Geo-Informatics (LSGI) is widely considered as a
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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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University of Massachusetts Medical School | Worcester, Massachusetts | United States | about 3 hours ago
Biology, Bioinformatics, Computer Science, Applied Mathematics, Statistics, Biophysics, Biomedical Engineering, or a related field. Strong programming skills in at least one of: Python, R, C/C++, or Perl
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of Electrical & Computer Engineering (ECE) invites you to apply for a 3-year researcher position (post doc level). Expected start date and duration of employment This is a 3–year position from April 1st 2026
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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 Science
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) at the University of Luxembourg contributes multidisciplinary expertise in the fields of Mathematics, Physics, Engineering, Computer Science, Life Sciences and Medicine. Through its dual mission of teaching and
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We offer a fully funded PhD student position within the Trustworthy Software Engineering (TruX) Research Group headed by Prof. Dr. Tegawendé F. Bissyandé. The position is embedded in a broader
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research program that brings together physics, chemistry, and machine learning. Your research tasks will include: Uncertainty Estimation in Deep Neural Networks for MLFFs Implement and test uncertainty-aware