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machine learning methods to investigate how ecosystem water stress and drought disturbances affect relevant forest ecosystem functioning at various scales. It will enable advanced assessment of forest
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computer science, engineering, information systems, economics, management, law, and other fields, united in pursuit of sustainable technologies that positively impact society. For more information, please visit our
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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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) - Three-dimensional conformally flat Lorentzian manifolds through experimentation (Karin Melnick) - Representation-theoretic methods in algebraic geometry (Karin Melnick & Pieter Belmans) - Computational
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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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The PhD position is embedded within the MICRO-PATH Doctoral Training Programme, funded by the Luxembourg National Research Fund. MICRO-PATH, or Pathogenesis in the Age of the Microbiome (https
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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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learning programme to foster our staff’s soft and technical skills Multicultural and international work environment with more than 50 nationalities represented in our workforce Diverse and inclusive work