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Code 8353NG Employee Class Civil Service Add to My Favorite Jobs Email this Job About the Job The University of Minnesota’s Center for Magnetic Resonance Research (CMRR) (http://www.cmrr.umn.edu/) has
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analytical and mathematical skills, including proficiency in quantitative modeling, data analysis, and scientific computing (e.g., R, Python). Strong written and verbal communication skills in English. *for
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-oriented research Requirements: strong programming and mathematical skills (or strong willingness to learning them) experience with Mathematica and Python work with models in public economics (e. g. optimal
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the Python programming language is an absolute requirement Experience with global vegetation models, satellite products (L3 or L4), and/or machine learning applied to spatially explicit data would be an asset
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offers an impressive benefits package. For more details on benefits, please see: https://hr.utexas.edu/prospective/benefits and https://hr.utexas.edu/current/services/my-total-rewards . For more
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programming languages (e.g., Python, shell scripting) or statistical analysis software (e.g., SPSS, SAS, R, MATLAB) is preferred. 6. Basic knowledge of statistics is preferred. 7. Electrical, mechanical
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tools, as well as server-side scripting (e.g., Python, PHP) and database systems (e.g., MySQL, SQL). Knowledge of digital accessibility standards, specifically WCAG 2.1 Level AA, and the ability to apply
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DC-26094– POSTDOC/DATA SCIENTIST – AI-DRIVEN CLIMATE RISK MODELLING AND EARLY WARNING SYSTEMS FOR...
: https://www.list.lu/ How will you contribute? You will be part of LIST’s Remote sensing and natural resources modelling group Embedded in the Environmental Sensing and Modelling (ENVISION) unit
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knowledge of programming, including Linux, Python, and R. Candidates having background knowledge in neuroimaging, machine learning, and/or genomics/genetics are encouraged. Excellent communication and writing
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Familiarity with use of Reference Managers Desirable Skills: Quantitative/Data Visualisation skills (Python?) Experience in data management Postgraduate or relevant research experience Works well within a team