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communication skills are also required. Desirable attributes include experience with PCM systems, bioenergy, IoT-based control, model predictive control, digital-twin development, prototype commissioning
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expertise in bioinformatics. The aim is to identify gene signatures predictive of therapy response and to discover novel therapeutic targets for reprogramming tumor-associated macrophages (TAMs)—immune cells
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computing, and digital twin technologies for mission autonomy and predictive analytics. The research assistant will develop real-time flight control algorithms, AI- based data processing, and mission
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National Aeronautics and Space Administration (NASA) | New York City, New York | United States | about 2 hours ago
list of Designated Countries can be found at: https://www.nasa.gov/oiir/export-control . Eligibility is currently open to: U.S. Citizens; U.S. Lawful Permanent Residents (LPR); Foreign Nationals eligible
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/Linux environment; - Good command of scientific English, both written and spoken (certified level). Website for additional job details https://emploi.cnrs.fr/Offres/CDD/UMR7285-CARNOE-068/Default.aspx
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for the original heat storage system developed as part of the Stock-HD project, integrated into a heating network. Intelligent control systems must be capable of predicting consumer demand profiles and adapting
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SUSMAT-RC - Postdoc Position in Computer-Aided Design and Discovery of Sustainable Polymer Materials
Materials Research Center (SusMat-RC) at UM6P. The successful candidate will work on an exciting project focused on extracting and analyzing experimental and computational data to develop predictive models
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(Lavrand et al., 2024) and GAG content (Scomazzon et al., 2021) on geometrically controlled structures is sufficient to modulate phase interaction phenomena. This will make it possible to distinguish between
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Job Description DTU Chemistry is seeking a talented researcher to develop advanced thermodynamic models for predicting phase equilibria and thermophysical properties of PFAS. This position offers
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evaluating adaptive Medium Access Control (MAC) and network‑layer protocols to enhance performance in shared spectrum environments. Developing AI‑driven methods for real‑time interference prediction and