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Field
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this goal, doped-diamond systems will be considered. The thermal stability of selected compounds under operating conditions will be assessed by means of molecular dynamics simulations with Machine Learning
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expertise from control theory, machine learning, optimization, and network science, spanning diverse application domains such as energy systems, biomedical systems, neuroscience, and safety and security
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related areas, with a special emphasis in the areas of Artificial Intelligence, Machine Learning and data models, in addition to app development; - If the candidate holds a higher education degree obtained
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practical applications, including solving mathematical reasoning problems. The ideal candidate has a strong background in machine learning and an interest in bridging rigorous theoretical insights with
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expertise. 2. Curriculum Vitae including a list of publications (maximum 3 pages). Where to apply Website https://jobrxiv.org/job/phd-position-in-machine-learning-and-ecology/?utm_sourc… Requirements
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is looking for an aspiring PhD candidate to research causal machine learning and uncertainty quantification for Earth Observation time-series. Currently, predictive AI in Earth Sciences relies heavily
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machine learning approaches Collaborating with experimental and clinical research partners Support and preparation of scientific reports and journal articles
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algorithms for asthma. The methods to be employed will include cell culture, transcriptomics, proteomics, multiplex assays, flow cytometry, and machine learning. This project combines expertise in cell biology
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stability analysis and control, machine learning, dimensionality reduction and high-performance computing. Where to apply Website https://emploi.cnrs.fr/Offres/Doctorant/UPR3346-NADMAA-159/Default.aspx
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Inria, the French national research institute for the digital sciences | Villers les Nancy, Lorraine | France | 6 days ago
Website https://jobs.inria.fr/public/classic/en/offres/2026-09928 Requirements Skills/Qualifications Profile: - The candidate is completing a Master's or engineering’s degree in Computer Vision, Electrical