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Time-Domain Spectroscopy, Hall measurements, Raman microscopy, device fabrication, Scanning Electron Microscopy, Instrument control in LabVIEW or python, synthesis of 2D materials, 2D materials
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. Experience using Python in a professional setting. Experience using data visualization tools (i.e. Tableau, Power BI or similar) Highly proficient in MS Office software with advanced knowledge of Excel. Strong
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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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methods, strong publication potential, good command of English, programming skills in MATLAB, Python, R, Julia, or similar. Experience in one or more of the following is an advantage: time series analysis
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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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mechanics) with data-driven techniques. • Proficiency in Python (NumPy, TensorFlow/PyTorch) and MATLAB. • Familiarity with deep learning architectures, particularly recurrent neural networks (e.g., LSTM) and
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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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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