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under uncertainty, programming in Python, Julia, and/or MATLAB, and excellent quantitative skills, including probability and data analysis. Anticipated Division of Time Research (80%) Publication
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primates or humans – Theoretical neuroscience, machine learning, or AI • Proficiency in Python, MATLAB, or equivalent data‑analysis frameworks. • A passion for big‑picture questions, open science, and
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and verbal communication skills in English • Proficiency in MATLAB and/or Python • Hands-on experience with rodent behavior and surgeries • Expertise in large-scale neurophysiology and histology
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policy pathways for electric power systems. Desired experience includes optimization and simulation of electric power systems under uncertainty, programming in Python, Julia, and/or MATLAB, and excellent
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acquisition and processing (Labview, Matlab/Simulink, C++ or Python). Technical competencies Knowledge of relevant technical/functional domains Relevant experience gained during internships, project work and/or
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or models) experience with computing languages such as python, R or MATLAB experience with presenting at conferences and writing manuscripts experience with leadership experienced at exhibiting independence
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simulation software, e.g., SUMO, MATSim, etc. Good command of a statistical or procedural programming language such as R, python, julia, matlab, etc. Interest in transport policy We offer We offer a full-time
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. • Preference may be given to applicants with experience with biological materials such as fungi, including culturing methods. • Basic experience with software such as MatLab, Python, or R for data visualization
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 14 days ago
of models and observational data using Python, Matlab, R, etc. Expertise required in developing new models, algorithms for dispersion, gas-phase chemistry and/or aerosol microphysics model Preferred
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 1 month ago
processes from multiple emissions sources as represented in current models, and quantitative analysis of models and observational data using Python, Matlab, R, etc. Expertise required in developing new models