31 parallel-computing-numerical-methods PhD positions at University of Luxembourg in Luxembourg
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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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, consider the usage of standards, and contribute to standardisation documents Present findings at international events The research activities will be hosted by the Parallel Computing and Optimisation Group
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society. For more information, please visit our website: https://www.uni.lu/snt-en/research-groups/finatrax/ The person will pursue a Ph.D. degree (Doctorate) in computer science and information system
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associated threats. The research project of the PhD student will thus focus on defining methods to track, monitor, and manage the use of GenAI. While this can rely on recentely proposed telemetry framework
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Pathogenesis in the age of the microbiome (MICRO-PATH; https://micro-path.uni.lu ) is a highly competitive, interdisciplinary, research-intensive PhD training programme, supported by the PRIDE
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Lorentzian manifolds through experimentation (Karin Melnick) - Representation-theoretic methods in algebraic geometry (Karin Melnick & Pieter Belmans) - Computational experiments with 3-dimensional hyperbolic
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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
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This position is inside the SPETRA doctoral training unit which investigates new materials, methods and concepts for converting sunlight into usable energy sources. Inorganic Chalcogenide
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diverse backgrounds (e.g., economics, computer science, information systems, engineering, etc.), united in pursuit of sustainable solutions that positively impact and shape a low-carbon economy and society
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methods for causal inference in observational data, is strongly preferred. Using various existing large datasets with rich information for knowledge synthetisation and triangulation over the course of the