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good knowledge of Python Experience with machine learning, in particular with neural networks and their implementation (PyTorch, TensorFlow or similar) Motivation and Initiative Residence in Berlin and
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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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Python and Fortran Familiarity with climate data formats (e.g. NetCDF) and relevant tools (e.g. xarray, CDO) Proficiency with Linux/Bash and Git version control Experience with HPC/supercomputing
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datasets • Contribute to data processing and analysis (R/Python; training provided as needed) Research Operations • Maintain study documentation and regulatory materials • Participate in lab meetings and
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state of the art AI and analytic tools (e.g., Go, Python, Rust, Spark, PyTorch, TensorFlow) to create consistent and reliable software. You will utilize tools and methods such as continuous integration
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or data analysis Training & experience in econometrics and causal inference methods, particularly in the context of randomized controlled trials (RCTs) Proficiency in R, Python, Stata, or similar tools
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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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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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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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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