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references; and draft brief evidence summaries to support study aims and methods. Develop/modify scripts in R/Python for data transformation, geocoding/linkage, and visualization using documented workflows
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University of Toronto | Downtown Toronto University of Toronto Harbord, Ontario | Canada | about 19 hours ago
information-hiding. Object-oriented programming. Specifications. Analyzing the efficiency of programs. Recursion. This course assumes programming experience in a language such as Python, C++, or Java, as
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or coding platforms including SketchUp, EnergyPlus, OpenStudio, TRNSYS, and Python; Proven ability to work at a fast pace and to react rapidly to new information; F1 experience would be advantageous but not
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(b) be proficient in data programming for data collection, textual analysis (Python, Stata or SAS) and English reading. Applicants are invited to contact Prof. Lisa C. Z. Sun at telephone number
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the development of data-driven insights and scholarly publications Position Requirements: Technical Proficiency: Strong command of Python or R for data manipulation (e.g., Pandas, Tidyverse) and SQL for database
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will have proven analytical problem-solving skills, experience in programming (Python, C++, or MATLAB), and evidence of contributions to peer-reviewed publications or technical outputs. Experience in
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. Qualifications Hands-on experience in data analysis An experience in astronomical/scientific data analysis is preferred. 1-year experience in Python programming is essential. (Required) Hands-on experience in data
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systems (Mojo, Julia, Rust, Python), and HPC system co‑design. This position is embedded within the larger DOE ASCR ecosystem, with direct relevance to ongoing efforts, and related AI‑for‑HPC thrusts
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in chemistry, physics, or related field. At least 2 years of experience developing quantum Monte Carlo algorithms. Strong problem-solving and analytical skills. Python programming experience. GPU
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, finance or computing science/natural language processing/machine learning. Preference will be given to those who are proficient in Python, adept at processing large-scale data and have worked with large