26 programming-"https:"-"https:"-"https:"-"CIPMM---Systemic-Neurophysiology" positions in Luxembourg
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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
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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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candidates in administrative, procedural, and regulatory matters Collaborate with the Doctoral Schools and the UL Competence Center to design and deliver onboarding and training programs for doctoral
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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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letter - addressing the following questions: (1) How does your background relate to the position? (2) How do you plan to contribute to the research project? (3) How does the position relate to your
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Applications should include: A copy of the academic degrees awarded and, where candidates are currently enrolled to an academic programme leading to a Master’s degree, the expected date
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of the BIVEC (the BeNeLux association for transport research) and as such it has free access to post-graduate courses also in other institutions in Belgium and the Netherlands. The training program
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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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clinical activity may be considered. Teaching: The holder of this position is expected to assist with the development and teaching in the Bachelor's programs in health (midwifery sciences, nursing sciences
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European grant requests related to study programs and lifelong training Compliance: Ensure compliance with university and national regulations in all grant-related activities Application Preparation: Assist