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pack levels. The successful candidate will contribute to research on lithium-ion and next-generation batteries, with emphasis on thermal runaway, predictive diagnostics, and mitigation strategies
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Are you a researcher driven to understand and predict the fundamental mechanisms limiting lithium-ion battery performance? We are recruiting a Research Associate in Lithium-Ion Battery Modelling
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National Aeronautics and Space Administration (NASA) | Greenbelt, Maryland | United States | about 5 hours ago
profiling (BGC-Argo) floats (https://www.nature.com/articles/s41586-021-03805-8). The NASA Ocean Biogeochemical Model (NOBM) has recently been coupled to the Subseasonal to Seasonal Prediction Version 3 (S2S
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. Specifically, your research will provide critical insight for NGGM performance assessment and predictions. You are encouraged to visit the ESA website: https://www.esa.int/ Field(s) of activity/research
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recognized for the work you do, and enjoy the unique value the CSUN community can offer. If this sounds like you, you’ve come to the right place. Learn more: https://www.csun.edu/about-csun . Major Duties
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, including device protection, impedance control and EMI mitigation; architect low‑inductance current paths, gate‑drive schemes (e.g., GaN/Si MOSFET drivers), and snubbers tailored to OLED stack constraints and
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: Textual Prediction of Survival (LLM classification & Attention Modelling) This project develops a model to predict patient survival by analyzing heterogeneous clinical documents. Unlike traditional methods
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opportunity to work in a top-tier interdisciplinary setting. This is what you will do You will develop predictive computational models to capture the formation and heterogeneous structure of microthrombi, with
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for corrective, preventive, and predictive maintenance activities. Serves as custodian of the facilities work control decision record, ensuring the integrity, traceability, and long-term accessibility of work
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. The work is part of the regional project “Optimizing Renewable Energy Integration: FPGA-Based Model Predictive Control (MPC) for Grid Stability” (Ref. SI4/PJI/2024-00238) Where to apply Website https