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processing approach based on flow patterning to make meter scale LCEs of complex shapes and actuation modes. ALCEMIST builds on a tight synergistic collaboration between the Experimental Soft Matter Physics
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innovative and creative research in theoretical quantum physics, including mathematical modeling and phenomenological and numerical analysis. The PhD student should display scientific ambition and target
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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 application is highly encouraged, as the applications will be processed upon reception. To ensure full...
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will pursue a Ph.D. degree (Doctorate) in computer science or software engineering with a focus on differential privacy (DP) and other secure computing techniques while collaborating with the Ministry
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website: https://wwwen.uni.lu/snt/research/finatrax/projects. The Ph.D. candidate will focus on information systems within computer science and engineering while collaborating with Luxembourg’s Ministry for
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Applications should include: Curriculum Vitae Cover letter A one-page research proposal (referencing the HOFA3 chapter) Transcript of academic records (including grades) and copies of diplomas Names and contact details of at least two references willing to write recommendation letters (they will...
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the impacts of various anonymization techniques from a business, legal and regulatory standpoint Designing and evaluating a reference process model to guide the implementation of legally compliant data
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on multiscale analysis of brain disorders with a focus on Parkinson’s and Alzheimer’s disease, and epilepsy by combining experimental and computational approaches. For a collaborative project within the Institute
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diverse backgrounds (e.g., economics, engineering, computer science, information systems, etc.), united in pursuit of sustainable solutions that positively impact and shape a low-carbon economy and society
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computational models and data analysis code to process large, multimodal behavioral datasets using both traditional methods (e.g., factor analysis) as well as more modern approaches (e.g., deep learning