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, machine learning, explainable artificial intelligence (XAI), digital twins, and integrated data-model approaches. • Study of the frugality of the developed approaches by reducing the requirements
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are seeking a candidate holding a Master 2 degree in computational biophysics, structural bioinformatics, or a related field. Knowledge of statistical mechanics and/or machine learning would be an asset
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modern machine-learning techniques, will be exploited to improve the discrimination between the different polarization states. The analysis will use the complete Run 2 and Run 3 datasets collected by
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computational fluid dynamics. • Experience in modeling, uncertainty quantification, or statistical methods. • Experience in data science or machine learning is considered an asset. • Experience with high
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spectrum of topics in CNU sections 27 "Computer Science" and 61 "Computer Engineering, Automation and Signal Processing". The laboratory is located at the heart of the Sophia Antipolis technology park, in a
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high-technology group operating in the aerospace, space, and defence sectors. The company designs, manufactures, and supports cutting-edge systems and equipment for civil and military applications. As
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computer, virtual data storage, and access to software tools for specialized data analysis (e.g., Cryo-EM data, crystallography, etc.). Structural microbiology: Exopolysaccharide secretion and host
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acquire in the course of the PhD skills in live microscopy, experimental neurobiology, genetics and behavioural work. The student will receive mentoring and have the chance to guide the research and
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of the professional environment: - Organization and functioning of higher education and public research; Operational skills: - Write reports or technical documents; - Use the computer tools necessary for the control
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remaining biologically interpretable? The PhD candidate will design and apply integrative computational workflows using methods such as multi-omics integration, spatial modelling, representation learning