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programming of algorithms. The use of programming languages such as Python, R, SQL, and C++ will be a daily part of the project, and proficiency in these languages is required. However, additional datasets will
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skills in data analysis, machine learning, as well as in mathematical and computational modelling? You will have the opportunity to investigate innovative solutions using machine learning algorithms and
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molecular targets critical for developing new therapies for rare diseases, based on genetic data and biological system simulations. -Computational Drug Repurposing: Developing novel algorithms and databases
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contributing to developing and implementing novel algorithms at the intersection of computational physics and machine learning for the data-driven discovery of physical models. You will be working primarily with
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algorithms, clinical decision support systems, and population health management platforms. Evaluate emerging technologies in clinical informatics and provide strategic recommendations for their adoption within
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(FSTM) at the University of Luxembourg contributes multidisciplinary expertise in the fields of Mathematics, Physics, Engineering, Computer Science, Life Sciences and Medicine. Through its dual mission
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classification for hyperspectral and fluorescence lifetime datasets. Optimize algorithms for batch processing and scalability, enabling high-throughput, automated analysis of large image datasets from fluorescence
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currently exploring a range of exciting topics at the intersection between computational neuroscience and probabilistic machine learning, in particular, to derive mechanistic insights from neural data. We
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. The HEXAPIC project aims to develop a novel high-performance Particle-In-Cell (PIC) code for plasma physics simulations, leveraging the capabilities of exascale computing systems. By optimizing PIC algorithms
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research environment focusing on integrating multi-source data and developing novel algorithms to address the challenges posed by global environmental change. You will focus on integrating experiments, field