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are expected to have a Ph.D. in theoretical particle physics or related areas prior to the time of employment. Preferences will be given to those with experiences in collider phenomenology, machine learning
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as an integrated analytical framework, we apply comparative risk assessment, disease modeling, machine learning, and survival extrapolation methods to systematically quantify the long-term impacts
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, with a strong interest in interdisciplinary research in biophysics. 2. Have a professional background in physics or mathematics or interdisciplinary biophysics, and experience in machine learning is
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administration or data analytics, such as Applied Psychology, Organisational Behaviour, Statistics, Machine Learning, and so on; Excellent oral and written communication skills in English, including the ability
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: Machine Learning / Machine Learning Lattice Field Theory lattice gauge theory Nuclear Theory Nuclear astrophysics Appl Deadline: 2026/02/01 11:59PM (posted 2025/11/04) Position Description: Apply
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discipline. Programming & Data Skills: Strong proficiency in Python (e.g., NumPy, Pandas, scikit-learn, PyTorch, TensorFlow); additional experience with R, MATLAB, or Julia is an advantage. Machine Learning
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: Quantum Computing / Quantum Computing High Energy Physics / accelerator , astrophysics , BSM , CMS , cosmology , Dark Matter , Experiment , Flavor Physics , Higgs physics , Lattice QCD , LHC , Machine
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(especially biomedical science, brain science, and neuroscience); data science and machine learning; modeling, analysis, simulation and prediction for biological, engineering, physical and quantum systems