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Field
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(dark matter, baryogenesis) and machine learning applications in these topics. The University of Oregon also has an experimental high energy physics group involved in the ATLAS experiment at the LHC and
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experiments for investigating the neural mechanisms underlying habitual behaviours and learning adaptation to uncertainty. You will use fMRI and neurostimulatory techniques (ultrasound neurostimulation and/or
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 2 days ago
the development and implementation of machine learning models Special Physical/Mental Requirements Special Instructions For information on UNC Postdoctoral Benefits and Services click here Quick Link https
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, Computational Linguistics, Machine learning, Computer Engineering or related fields Preferred Qualifications: ● Strong experience implementing and training deep learning models in PyTorch, with attention
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and others) Analysis of the experimental data, ideally connecting to our machine learning tools Presentation of scientific results on conferences and in publications Requirements PhD degree in physics
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-Doctoral Research Associates and PhD students. To find out more go to: Centre for Integrated Renewable Energy Generation and Supply - Research - Cardiff University https://www.linkedin.com/showcase/centre
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transitions and universality for spectral statistics of random matrices and their applications in high-dimensional statistics, machine learning and probability theory. The Department of Mathematics at KTH
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written and spoken Willingness to engage in interdisciplinary collaboration and fieldwork Advantageous: Knowledge of bat ecology and species identification Experience with machine learning or automated
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, learning under uncertainty) that is of an international standard, and that is carried out expertly, rigorously and in accordance with ethical guidelines. You will also participate actively in the lab
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-XRF, Raman, FTIR in reflection mode) to enable multimodal data fusion and automated material characterization. • Apply and further develop machine-learning and statistical models (e.g. PCA, SAM