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, that combines diffusion and transformer models, there are clear indications that the analysis of this data can be automated. This will open new avenues in data interpretation and building predictive models
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research environment is highly collaborative and interdisciplinary, spanning genome biology, computational analysis, and translational cancer research. Members of the lab gain expertise in next-generation
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two-dimensional (2D) materials such as graphene, a-RuCl3, and transition metal dichalcogenides (TMDs). This PhD project is highly focused on methodology, resolution enhancement, and reproducibility. It
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experiments utilizing state-of-the-art approaches such as: Animal models of metabolic diseases and atherosclerosis Flow cytometric analysis of immune cell populations from murine tissues using full spectrum
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disturbances on OFR using visual media (e.g., photos, videos). The supply and demand of OFR will be assessed via a spatial analysis to identify recreational hotspots and inform forest management of them. Finally
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, with exciting collaborative opportunities globally, as well as within Luxembourg. The doctoral candidate will perform wet lab experiments as well as computational analysis to uncover biophysical
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work on crypto-asset transaction analysis - at the intersection of data science, blockchain technology, and financial crime prevention from an Anti-Money Laundering and Countering the Financing
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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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perturbations. Climate and human-induced disturbances may alter forest ecosystems dynamics, modifying eventually their resilience to rapidly changing conditions. Previous studies based on the temporal analysis
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for Neurosciences, Biophysics, and Molecular Biosciences (GGNB). The MINFLUX and MINSTED concepts have unlocked the door to minimally invasive, low-light-level analysis of the structure and dynamics of macromolecules