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heavy ion beams at the accelerator facilities in Germany and China. We also initiated and lead the project to study hypernuclei by analyzing the nuclear emulsion data with machine learning techniques. We
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-based modeling of hydrological and Earth system processes. The CHAS group conducts world-class research in hydrological and Earth system modeling, large-scale data analytics and machine learning (ML), and
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for generations to come. To learn more about SEAS and our values, please visit our website at https://seas.umich.edu/about/seas-values. Why Work at Michigan? In addition to a career filled with purpose and
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coupled hydrological and groundwater modelling, combined with machine learning techniques, will quantify groundwater recharge and groundwater resilience. Your responsibilities: Analyse the dynamics
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are proficiency in Python, deep learning frameworks such as Keras, PyTorch, TensorFlow, or other related software stacks, and a solid background in machine learning, cybersecurity, or AI robotics, and the ability
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of faculty at SUNY Polytechnic Institute and the University of South Florida, consisting of mathematicians, physicists, computer scientists, and engineers investigating applications of deep learning
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areas: -developmental biology -experimental and/or theoretical biophysics -experimental and/or computational genomics -computer science, statistics, and/or machine learning with applications relevant
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The University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 3 months ago
efforts with other laboratories will be promoted to allow the RA to learn new techniques. Education and Experience: Complete several different tasks simultaneously and have excellent time management skills
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Your Job: As part of an interdisciplinary project team with researchers from bioinformatics you will work on quantum algorithms for drug discovery. Here, the focus lies on machine learning and
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emerging spectrum (FR3, MMW, sub-THz/THz) Extreme massive MIMO communications Analog, digital and hybrid beamforming architectures Reconfigurable intelligent surfaces Machine learning for wireless