31 python-"https:"-"CIPMM---Systemic-Neurophysiology" positions at Cornell University
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interactive projects is desirable. Candidates should be able to teach (instruction as well as laboratory experiences) comfortably and competently on at least the following subjects: C and Python programming
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desirable. Candidates should be able to teach (instruction as well as laboratory experiences) comfortably and competently on at least the following subjects: C and Python programming; digital logic and SoC
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tools are required. Robust modelling and programming abilities (e.g., Python) are essential prerequisites. Experience with VIC (or similar hydrologic models), GIS, and large-scale computing—particularly
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are welcome, but strong data-analytics skills and solid knowledge of process-based numerical modelling tools are required. Robust modelling and programming abilities (e.g., Python) are essential prerequisites
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, distributed computing, and geospatial data processing • Python, R, SQL/NoSQL, containerization (Docker), Kubernetes • API development and web-based analytics tools • Systems, Optimization, and AI • ML/AI
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demand forecasting or behavior modeling Computing & Data Systems Cloud computing (AWS, Azure, GCP) Big data pipelines, distributed computing, and geospatial data processing Python, R, SQL/NoSQL
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(Python, R) and database systems • Strong analytical and problem-solving skills • Ability to manage multiple projects and collaborate effectively • Familiarity with CI/CD pipelines, DevOps practices, and
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pre-doctoral research fellow will work closely with one or more faculty whose research interests fall within the broad domain of development economics. The CIDER faculty can be found at https
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-driven systems Demonstrated proficiency in at least one major programming language commonly used in AI/ML and scientific computing (e.g., Python), including use of modern software engineering practices
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Information Technology, or a related field • Evidence of high-quality research productivity (publications, presentations, software, system prototypes) • Strong analytical and computational skills (e.g., Python, R