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contributing to multiple projects including resilience-aware scheduling, deep learning workload job scheduling, and storage system performance tuning. The candidate will have the opportunity to engage in
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modeling, machine learning, and experimental studies, while offering the opportunity to contribute to open-source libraries and collaborate directly with an innovative startup partner. You will be
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on understanding the spread and control of human infectious diseases using modelling and pathogen genomics. This is a short-term opportunity to apply machine learning methods to two key projects. First, you will
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information, remote sensing data, and GIS software. Experience in deep learning and computer vision. Experience in developing software tools and products. Experience in writing scientific papers and successful
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. The Plutonium-238 Supply Program at ORNL is producing plutonium-238 for NASA in support of powering deep space missions. To do so, a myriad of chemical processing steps are required to prepare targets
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school with deep roots in the Nordic socio-economic model. Our faculty has a broad focus on societal challenges, and we have earned a reputation for high-quality disciplinary and interdisciplinary research
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. Posting Summary The Department of Statistics in the School of Arts and Sciences is seeking a Post Doctoral Associate. The successful candidate should have deep knowledge and experiences conducting research
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: Develop and implement machine learning algorithms for SOC and SOH estimation. Analyze large datasets from battery systems to improve model accuracy and performance. Conduct research on predictive analytics
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chemical discoveries for renewable energy, biomedicine, and other areas of societal importance. Coding and/or machine learning experiences are highly valued. Specific projects may involve developing
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Your profile The successful candidate will pursue a second book / "Habilitation" research project, teach courses, contribute to the Department's profile areas "Premodern History" and "History