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join the group to develop AI and machine learning based software to assist clinical workflow and pre-clinical studies. Required Qualifications: Ph.D. in a physical science or engineering field Strong
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e.g., ultra-cold gases of bosonic or fermionic atoms, machine learning technologies and quantum computing. At the same time, we work in close connection with IJCLab experimentalists, particularly
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the CARINA project which is funded through a Research Ireland Frontiers of the Future grant. CARINA stands for Combining Machine Learning with Forefront Astronomical Instrumentation to Probe Intermediate Mass
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Postdoctoral Associate to work on a fascinating project focused on the development machine-learning powered digital twin system for the structural performance of civil engineering structures. The project is a
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of memory, ageing, and the effect of Alzheimer’s Disease risk factors on midlife brain function and cognition. The applicant should be interested in applying multivariate and machine learning neuroimaging
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care for patients requiring urgent or emergent intervention. The fellowship provides comprehensive training in data engineering, exploratory analysis, statistical modeling, machine learning, and artificial
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in the United States. Preferred methodological skills include statistical analysis of survey and other large-n data, qualitative interviews, and/or text analysis and machine learning skills
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development spanning areas such as optimization, Fourier analysis, numerical linear algebra, statistics, machine learning, and high-performance computing for one or more of the following: (1) reconstruction
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courses (approximately two courses per year). Additionally, they will assess the effectiveness of these strategies on student engagement, learning outcomes and sense of belonging. The Postdoctoral Associate
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for this position will work as a member of an interdisciplinary team led by Dr. Colin Xu on Department of Defense (DoD)-funded research project involving the use of statistical and machine learning methods