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collaborative opportunities globally, as well as within Luxembourg. The doctoral candidate will perform wet lab experiments as well as computational analysis to uncover biophysical principles that regulate host
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and Innovation, the successful candidate will work on crypto-asset transaction analysis - at the intersection of data science, blockchain technology, and financial crime prevention from an Anti-Money
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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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well as computational analysis to uncover biophysical principles that regulate host-pathogen interactions and feedback, using a combination of quantitative imaging, microfluidics, statistical analysis and machine
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commercial simulation tools such as Abaqus and Comsol Multiphysics. o Familiarity with multi-scale or coupled field analysis (e.g., structural-electromagnetic, fluid-structure). o Understanding of drone
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. Activities of the successful candidate: Conduct extensive background literature analysis. Plan and organise experiments to define and test hypotheses and develop forefront research. Publish the results
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analysis (R, Python) is an asset. Curiosity, creativity, rigor, willingness to learn, team spirit and collaborative capacity, excellent time and priority management. Fluency in English (written and spoken
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in a number of the following topics: Turbulence modeling with wave propagation simulations Modulations used in optical wireless communications Data Analysis and Management Implement and open-source
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: · Processing multi- and hyperspectral satellite and drone data · Collection of field data on relevant forest traits and laboratory analysis · Forest radiative transfer modelling · Hybrid
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, and multi-level data analysis Communicate and collaborate with a research team, including teachers and student assistants Engage in international opportunities for learning and development (i.e