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for many high-tech companies. Job description This role involves the development of cutting-edge chemical sensors based on metal-organic frameworks (MOFs) that leverage kinetic selectivity to differentiate
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are linked to research on composite hydrogen tanks, composite propellers for drones and finite element modelling of textile manufacturing. All research will be conducted with leading companies in
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pathway. Additionally, finite element theoretical modelling and density functional theory calculations will be used to further increase our understanding of the photo-reduction mechanism. Correlating
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Directed Energy Deposition (DED) process for metallic components. The PhD candidate will focus on edge computing and the application of AI for data analysis and for identifying correlations with ground truth
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motion) Pose tracking and behavior segmentation with tools like DeepLabCut, MoSeq, and Kinect-based systems Longitudinal analysis of behavior from early postnatal to adolescent stages in
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motion) Pose tracking and behavior segmentation with tools like DeepLabCut, MoSeq, and Kinect-based systems Longitudinal analysis of behavior from early postnatal to adolescent stages in
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the following elements: Abstract (max 250 words) The abstract of a PhD research plan should serve as a concise summary of the key elements of your proposed research. It should provide an overview
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factors that accelerate material deterioration (e.g., hydrogen embrittlement, corrosion). The primary tasks include developing advanced multiphysics frameworks (finite element/phase-field methods
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live in. Your role The PhD project will focus on Energy Sector Coupling, a key component of the energy transition. In collaboration with an industrial partner - a major energy player in Luxembourg - you
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, qPCR, digital PCR, amongst others. Sequencing data analysis will be done using data analysis pipelines (Python, R) on the high-performance computing (HPC) infrastructure. About the TOBI lab