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Field
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of decarbonization 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
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EEG, brain stimulation, or data science methods Track record of conference presentations and peer-reviewed publications Strong verbal and written communication skills Proficiency in R, Matlab, or Python
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computer programming tools such as Matlab and/or Python. Knowledge of statistics and mathematical modeling. Experience in large spatial data processing, analysis, and interpretation. Experience in running
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, psychology, or equivalent statistical genetics expertise and hands-on experience with high performance computing and big data analysis skills in programming and scripting languages (R/Python/Matlab) excellent
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minimum of one year eligibility remaining. • Self-motivated and able to work independently and collaboratively • Strong communication skills • Proficiency in R, Python, or MATLAB • Familiarity with
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programming skills and finite element (FE) analysis experience is a requirement. Knowledge of machine learning, Matlab and Abaqus is also highly desired. Previous experience with parametrization and automation
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. Proven expertise in microgrid modeling and controls in Matlab/Simulink or similar Demonstrated publication record Proven communication, time management, and teamwork skills This project is funded by
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knowledge in bioinformatics, machine learning, statistics and programming skills (R, Python, or MATLAB) are required. The ideal candidate should demonstrate a record of publications in the area. Knowledge in
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, or MATLAB) are required. Knowledge in one or more of the following areas is desirable: biomedical imaging, biomedical optics, computer vision, bioinformatics, single-cell profiling technologies, spatial omics
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; supervising student projects/practicals. · Demonstrable ability to model experiments using a range of software packages, such as Python, Matlab or Mathematica. · Experience of experimental