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Field
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leverages the latest advancements in artificial intelligence/ machine learning (AI/ML) and high-performance computing to accelerate the discovery, design and synthesis of advanced functional materials
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. Therefore, this position is contingent upon continuation of funding from these grants and/or contracts, as well as satisfactory job performance. What You Need to Do Apply! Applicants are encouraged to upload
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knowledge of computer and system architecture, as well as performance engineering. • Pleasure in taking responsibility, independent and structured way of working, high commitment, communi-cation and team
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will develop FEM technique to quantitatively characterize amorphous materials, with high spatial and temporal resolution. * You will be part of a team performing experiments to lead the discovery of key
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and modelling of nanoelectronic devices operating at cryogenic temperatures (4 Kelvin - 77 Kelvin) for energy efficient quantum computing (QC) and high-performance AI computing in data centres
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physics such as materials physics, photonics, computational physics, high energy physics, atomic and nuclear physics, plasma physics, theoretical and quantum physics, and astrophysics. With approximately 20
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synthetic and additional characterization needs. High-performance computing facilities will also be made available and the successful candidate will use density functional theory calculations to predict
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techniques to control the growth environment and material consistency across the wafer targeting applications in microelectronics and quantum information science. This position resides in the Functional Hybrid