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Field
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of materials. We are searching for a Postdoctoral Researcher with excellent numerical skills and a deep understanding of condensed-matter physics concepts. Experience in machine learning, DFT, symmetry aware
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highly stimulating environment that engages the best and brightest faculty and students to conduct deep and impactful research. Our faculty's research expertise and strengths cover several key
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assisting with in-situ TEM measurements, facilitating cutting-edge research in sustainability and energy fields. Part of the project will also include the development of deep learning frameworks for TEM image
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future. Fueled by curiosity and a deep sense of duty, they contribute invaluable insights to research and teaching, enriching our society. Are you inspired and driven by the desire to make a meaningful
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spectral imaging, lifetime data, or multi-channel image datasets. Solid background in chemometrics, machine learning, or deep learning, particularly for classification, clustering, or pattern recognition in
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intelligence (including machine learning). Desired Qualifications Publications in health sciences and biomedical journals. Demonstrable interdisciplinary research experience. Deep understanding of machine
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with the Neurosurgical Department at the University of Iowa (with whom we perform intracranial LFP recordings from deep-brain regions as well as sEEG), the Neuropsychology Group in the Department
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seeking applicants with experience in: Radial velocity, stellar, and/or exoplanet spectroscopy studies; and/or astronomical instrumentation or observing programmes Machine learning in physical science
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focuses on single-cell genomics, biotechnology, and bioinformatics. The project involves transcriptomic and genomic profiling of single microbes. The post-doc will work on machine and deep learning methods
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the Department of Physics. Machine learning has made enormous progress during recent years, entering almost all spheres of technology, economy and our everyday life. Machines perform comparably to, or even surpass