17 parallel-programming-"Multiple"-"Humboldt-Stiftung-Foundation" PhD scholarships at University of Luxembourg
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As a part of this collaborative research programme, you will join as one of three PhD candidates working on interconnected projects in Quantum Optimisation, People-Centred Design (PCD
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extended from cloud solutions (such as OpenLLMetry), the research question is how to identify anomalies in collected information that can come from multiple AI services either invoked manually by users or by
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to evaluate. The main research question is how to automatically harmonize the retrieved information allowing a unique analysis and to map them against multiple user-tailored outputs. This is necessary as the
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environment for PhD candidates, with multiple seminars, working groups, colloquia, and a doctoral school, which also gives access to multiple training opportunities, including courses on general research skills
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use by the group employ multiple-input multiple-output (MIMO) technology and can be connected to build a distributed and cooperative network. To develop signal processing techniques, the group
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research the Growing schools; Growing futures initiative, thereby contributing to the research program of the SciTeach Center team, led by Prof. Dr. Christina Siry. The PhD candidate will engage in
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). This project aims to accelerate the energy transition in Luxembourg by co-creating an ambitious research program. It will utilize a data-driven approach to support decision-making for an optimal energy system
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). This project aims to accelerate the energy transition in Luxembourg by co-creating an ambitious research program. It will utilize a data-driven approach to support decision-making for an optimal energy system
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& Applications. The "Technical Standardisation for Trustworthy and Sustainable ICT, Construction, and Aerospace" research programme represents a strategic collaboration between Luxembourg Institute
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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