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neural networks) to predict materials properties (e.g. ionic conductivity, stability). Communicate and present findings in team meetings, research fairs conferences (with support from the professor
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Max Planck Institute for Nuclear Physics, Heidelberg | Heidelberg, Baden W rttemberg | Germany | 6 days ago
Job Code: 15-2026 Job Offer from September 24, 2026 The Max Planck Institute for Nuclear Physics is one of 85 research institutes of the Max Planck Society for the Advancement of Science e.V. (MPG
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refrigeration systems, including but not limited to, water source heat pumps, direct expansion, and electrical, plumbing systems. Ensure all components adhere to national and state codes. Perform preventative
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Inria, the French national research institute for the digital sciences | Villeneuve la Garenne, le de France | France | about 20 hours ago
to improve our ability to predict the effectiveness of an ordering heuristic based on the properties of problem instances. In this project, we will primarily focus on the analysis of ordering
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-Doctoral candidate to join our research team. Your research focus will be on the experimentation of real-time robust model predictive control schemes for induction welding. As a first step you will be
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National Aeronautics and Space Administration (NASA) | Merritt Island, Florida | United States | about 11 hours ago
Organization National Aeronautics and Space Administration (NASA) Reference Code 0006-NPP-NOV26-KSC-Interdisc How to Apply All applications must be submitted in Zintellect Please visit the NASA
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covering discovery of new therapeutic mechanisms for complex diseases, early detection of pathologies, and comprehensive prevalence and prediction of pathologies, all based on the mechanistical understanding
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are you going to do? The project addresses a central question in mechanobiology: how do cells sense, encode and respond to mechanical cues? You will develop a quantitative and predictive framework
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genetics/genomics. More about the position The project aims to develop novel computational methods and tools for predicting functional non-coding mutations in the cancer genome. These methods will integrate
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improve access to divertor-relevant target exposure conditions. Validate simulation results against experimental data and constrain code inputs to reduce uncertainty in predictions for future experiments