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Field
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experimentation and thermodynamics calculations. Establish a high-throughput bulk materials processing route to enable efficient characterisation and parallel testing of multiple compositions. Develop a high
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well as travel to and present at those events where appropriate. Current projects include: parallel numerical optimization with a focus on GPU acceleration, efficient embedded edge computing and machine learning
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experimentation and thermodynamics calculations. Establish a high-throughput bulk materials processing route to enable efficient characterisation and parallel testing of multiple compositions. Develop a high
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of computational platforms. We also want to improve the accessibility of STEM education. We therefore undertake research at the intersection of Robotics and Computer Architecture, Embedded Systems
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Argonne’s core values of impact, safety, respect, integrity, and teamwork Preferred Skills and Qualifications: Experience with high-performance computing and parallel computing Familiarity with data
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Data Management and Network/Computing ContinuumCloud computing has significantly increased the volume of data consumed daily, but it has also centralized somehow the storage of data. With
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with Python and R programming languages. Experience with functional genomic technologies including massively parallel reporter assays. Biomedical informatics or biomedical research experience. Preferred
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frameworks (e.g. PyTorch, TensorFlow) and relevant libraries. Practical experience in scalable data processing, including the use of parallel computing, cloud platforms, and distributed systems for efficient
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insights from related small models, and employ distributed optimisation and parallel computing to investigate knowledge transfer and interaction between small and large models; (b) assist in general
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for the quality of its medical expertise, facilities and teaching. The Neuroscience and the Mental Health Program is one of the leading research programs in the medical school. The key objective is to conduct both