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(KCL, London, UK) but will also have the opportunity to travel and work at the Centre for AI and Machine Learning (ECU, Perth, AU) and the School of Psychiatry and Clinical Neuroscience (UWA, Perth, AU
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, including use of scientific libraries (e.g., NumPy, Pandas, Matplotlib, etc). Experience with machine learning (e.g., Scikit-learn, PyTorch) or physics-informed neural networks for thermal systems is a plus
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well as building competence to relate professionally to religious and worldview diversity for individuals in public service such as administration, health care, correctional facilities or the armed forces
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considers factors such as (but not limited to) the specific grant funding and the terms of the research grant when extending an offer. PhD apply on Interfolio site For people in the EU, click here
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National Aeronautics and Space Administration (NASA) | Pasadena, California | United States | 5 days ago
://doi.org/10.3389/fenvs.2025.1473890 Madani, N., et al., & Miller, C. E. (2024). A machine learning approach to produce a continuous solar-induced chlorophyll fluorescence dataset for understanding Arctic
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, LHC , Machine Learning , Neutrino , Neutrino physics and Astrophysics , Phenomenology , Quantum Field Theory , Theoretical Particle Physics , theory , Lattice QCD Appl Deadline: 2025/12/01 11:59PM
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performs MRI research and development of advanced multiparametric methods for the evaluation of primary and metastatic brain tumors. Recent work incorporates machine learning methods to advance
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be the continuation of previous work, would use machine learning on a simulated data base to define the tool, followed by an application to real data from GRAVITY/VLTI (K band), MATISSE/VLTI (L, M, N
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Oxford’s Department of Orthopaedics (NDORMS) as well as collaborators in Bristol and Cardiff. You should have a PhD/DPhil (or be near completion) in robotics, computer vision, machine learning or a closely
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postdoctoral and PhD researchers on the team*Interest in developing and applying Large Language Models (LLM) and spatial Machine Learning (ML) modelsSalary and full employee benefits are offered in accordance