157 computer-programmer-"https:" "https:" "UNIS" "https:" "https:" "https:" "https:" "I.E" positions at University of Luxembourg
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, the DHML is offering candidates a range of opportunities to access leadership positions, including study programme directors and domain coordinators, according to the needs and development of the medical
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of Life Sciences and Medicine (DLSM). The successful candidate will establish and lead an internationally recognized, independent pharmacological research programme in an area of biomedical relevance
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In 2023, the University launched four bachelor programmes in specialized nursing sciences in the fields of surgery, anaesthesia/resuscitation, paediatrics, and mental health. A fifth programme
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of Luxembourg Competence Centre, Language Centre, Cultural Affairs, Institute for Innovative Teaching and Learning), as well as the Student Delegation, Student Associations, Study Programme Representatives
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the development of a higher-layer semantic planning, the decomposition of the plan in subsegments and dedicated controller (such as MPC) for combined planning and control on a subsegment of the XS-Graph
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teaching programmes in medicine, life sciences, nursing, radiography and midwifery. Research at the department integrates basic and translational, molecular and computational approaches with a focus on
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Environmental Engineering area, active in structural and infrastructural research, and funded by national/international programmes and partnerships. Some members contribute to EUROCODE development. The candidate
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with the nano-drones of the University’s SwarmLab The research activities will be hosted by the Parallel Computing and Optimisation Group (PCOG) at SnT, headed by Prof. Grégoire Danoy. PCOG conducts
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The Department of Finance at the University of Luxembourg invites students to apply for Doctoral researcher positions in Finance. The program follows the standard international format with rigorous
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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