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(e.g., economics, business, technology), united in pursuit of sustainable solutions that positively impact and shape a low-carbon economy and society. For more information, please visit our website
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Autonomous Transportation. As far as technical enablers are concerned, we leverage expertise on advanced technologies including semantic/task-oriented data processing, signal processing, network resource
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promotes an inclusive culture. We encourage applications from individuals of all backgrounds and are dedicated to upholding equality and respect for our employees and students. General information: Contract
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photopolymerization of the precursor. The practical work will be complemented by fluid mechanics computer simulations, including solutions employing machine learning, and theoretical analysis using Leslie-Ericksen
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momentary assessment) and the combination of self-report and sensor-measured data. There will also be the opportunity to contribute to longitudinal survey studies and analyze existing datasets. The person is
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of a combination of multi-omics data from the gut microbiomes of patients with Alzheimer’s disease or Parkinson’s disease. The candidate will use state-of-the-art in silico protein structure prediction
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Applications should include: Curriculum Vitae Cover letter Contact information of two or three referees Research statement and topics of particular interest to the candidate (max 1 page) Early
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The successful candidate will join the CritiX research group (https://www.uni.lu/snt-en/research-groups/CRITIX/ ) headed by Prof. Marcus Völp. The team focuses on critical information
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, which will collect detailed information on the dynamics of stress reactivity, but also on positive experiences and the role of strengths and weaknesses in the everyday lives of the very old. The candidate
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We are looking for a doctoral candidate with a strong computational, engineering, data scientific or machine learning background that is keen to work in an interdisciplinary environment and open to