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Field
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for extracting physiological biomarkers from ECG, PPG, and related sensor data Machine learning and AI for predictive modelling and risk stratification Computational physiology modelling to personalise and
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data analysis is required, particularly in the handling and interpretation of data arising from physical experiments or computational models relevant to nanoscience. Teamwork; Critical thinking and
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create a working framework that includes both experimental and modelling prototypes, including AI/ML tools to assist with the large number of variables involved. This project is seeking candidates with a
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job funded through the EU Research Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description The twin crises
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genetic, phenotypic, and environmental data, testing when and how evolution can be forecast. As a PhD student in our group, you will gain hands-on experience in computational and mathematical modeling and
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statistical analyses on large databases Designing and running experiments Structural modelling and related econometrics Proving theoretical results Basic Qualifications Bachelor’s degree by start date (required
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explore how to combine data-driven and model-based approaches to assess the quality of returned parts, monitor in-process performance in real time, and support intelligent decisions on remanufacturing
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Applications are invited for a Senior Researcher in Decision Analytic Modelling, working with Associate Professors Apostolos Tsiachristas and Brian Nicholson, on a research programme developing and
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2 Sep 2025 Job Information Organisation/Company CNRS Department Maison de la Simulation Research Field Computer science Mathematics » Algorithms Researcher Profile Recognised Researcher (R2) Country
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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