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Performance . About You The successful candidate will play a key role in the development and validation of computational tools that integrate spatial transcriptomics, algorithmic methods, and machine learning
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, modular battery with machine learning algorithms. The aim is to develop a high-performance, intelligent battery system that includes advanced thermal management and high-performance battery management
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effect prediction. The fellow will work under the mentorship of Dr. Alex Luedtke and collaborate with an interdisciplinary team of statisticians, physicians, computer scientists, and health policy
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characterization techniques (e.g., Micro-CT, XRD, SEM, EDS, EBSD, TEM) and (5) mechanical performance qualification (e.g., hardness, tensile, fatigue, high strain rate) in simulated operational conditions to assess
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skills. Demonstrated ability to work independently and as part of a team with minimal supervision. Demonstrated capacity to deliver high-quality project outcomes in a timely manner. Computer programming
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Independent definition, development and implementation of processes for transferring promising laboratory concepts into the 300 mm high-tech cleanroom environment Optimization of process flows and metallization
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effect prediction. The fellow will work under the mentorship of Dr. Alex Luedtke and collaborate with an interdisciplinary team of statisticians, physicians, computer scientists, and health policy
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, biomedical or computational imaging). A detailed knowledge of molecular imaging, or material science is mandatory. Experience in designing and performing scientific work independently and collaboratively is a
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The National Energy Research Scientific Computing Center (NERSC ) at Berkeley Lab seeks a highly motivated Postdoctoral Researcher — Scientific Machine Learning (NESAP) to join the Workflow
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the Job related to staff position within a Research Infrastructure? No Offer Description The candidate will develop and employ a variety of computational biology techniques to perform antibody design