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Performance Computing environment, and utilization of bioinformatics pipelines. Translational Research: You will learn how to translate fundamental research findings into practical solutions for U.S
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both the academia and the industry to lead and/or conduct innovative research on applied artificial intelligence computing. Contribute to academic research in the relevant domains and publish high-tier
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interdisciplinary advantage to shape the future. Our social mission is to provide research-based education of high quality, perform artistic development and carry out research of the highest international quality
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educational and research opportunities. This includes participating in relevant committees, conferences, and professional activities. Primary goal is to ensure that the program provides high-quality education
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experimental and operational data, evaluating machine performance, and preparing high-quality technical reports for industrial partners. The Research Fellow will also be expected to contribute to the wider
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experiments, and evaluate and compare their performance. Qualifications and personal qualities Applicants must hold a master's degree or equivalent education in mathematics or in computer science with a
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machine learning methods for computational materials physics and chemistry. Projects include: The aim is to develop generalized equivariant neural network models NequIP and Allegro for machine learned
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national and international stage. At UQ, you’ll enjoy a supportive, inclusive and high‑performing environment that empowers you to grow your research profile, supervise emerging researchers and make a
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, and building computational engines. The postdoctoral fellow will be hired for a one-year position with opportunity for renewal on a yearly basis assuming satisfactory performance. The positions include
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Postdoctoral Fellow with Professor Morgane Austern. Professor Austern’s group focuses on research in high-dimensional statistics, probability theory, machine learning theory, graph data, Stein method, ergodic