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continuous improvement initiatives to enhance data accuracy, accessibility, workflows, and business impact. Engage with and leverage AI tools to optimize financial work flows, analysis, and decision making
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computational algorithm(s), perform data analysis, collaborate with biologists and physicians. He or she will lead multiple projects, work in a multidisciplinary environment and present/publish the results in
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Team leader with a high degree of knowledge in the overall field and recognized expertise in specific areas; problem-solving frequently requires analysis of unique issues/ problems without precedent
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industry in our research work. We seek a motivated candidate who is keen on rigorous research, the practical applications of code exfiltration and reverse engineering as well as security penetration testing
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Start date: 1 July 2026 or as soon as possible thereafter. Part time, fixed term: Two months at 0.5 FTE (but can be flexible between 1 month at 1FTE and 6 months 0.16 FTE) Applications are sought
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Job Purpose To make a leading contribution to discovery and translational research exploring the role of creatine and homoarginine in cardiovascular health and disease. The post is laboratory based
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, participatory, and stakeholder-facing aspects of the project. They will design and run co-design workshops, contribute to analysis and evaluation, and work closely with technical and clinical partners
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applications in AI and data analytics. Performance evaluation and scalability analysis of frameworks used to process large-scale datasets (NET4EXA). Stakeholder mapping and engagement activities in WP6 RI-SCALE
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National Aeronautics and Space Administration (NASA) | Greenbelt, Maryland | United States | about 5 hours ago
. Description: This opportunity is closed to applicants who are Senior Fellows (5-years or more past PhD). The Goddard Earth Observing System (GEOS), developed by NASA’s Global Modeling and Assimilation Office
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laboratoire. L'algorithme final a montré de très bons résultats sur des données de simulations et sur des données expérimentales (https://doi.org/10.1364/OL.566273 ). Cependant, cette approche requière une