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with Bayesian inference or machine learning is an advantage. • Proficiency in Python and/or R; experience with probabilistic programming (Stan, PyMC, NumPyro) or deep learning frameworks (PyTorch, JAX
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of experience in logistics and supply chain management is an advantage. Those without relevant work experience but who have the technical skills are welcome to apply. Proficiency in Python or similar programming
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datasets, registries, or electronic medical records • Strong knowledge of causal inference and comparative effectiveness methods • Experience using statistical software such as R, Stata, SAS, or Python
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issues. Proficiency in urban modeling tools such as MATLAB, Python (especially libraries like Pandas, NumPy, SciPy, GeoPandas, etc.), and R. Advanced skills in predictive modeling and machine learning
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. Performs advanced signal processing and time–frequency analyses of neural recordings. Develops and implements computational pipelines using MATLAB, Python, or similar platforms. Leads manuscript preparation
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ends 8/31/2026. Required Qualifications The person applying for this position should be proficient in Excel, Python or MATLAB. Desired Qualifications Training provided. Special Instructions to Applicants
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of Miami. Other potential undergraduate classes include Introduction to Python Programming - a requirement for the Rosenstiel BS - and Climate Change, a general education course. We are also considering
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, retrieval products) Strong programming skills in Python Experience in machine learning, ideally including deep learning architectures such as graph neural networks, transformers, or spatio-temporal models
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skills Ability to work with nuclear industry data Good understanding of the nuclear sector in Canada Proficiency in at least one programming or statistical software package (Python, MATLAB, R, or Stata
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analytic workflows on an active NIH-funded research grant. Applicants should have a bachelor’s degree in an analytic field (data science, AI, or bioinformatics) and demonstrate familiarity with R and Python