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Field
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) software application primarily supported by the UIS eRA team and the Grants suite of modules from PeopleSoft Financials and Supply Chain system supported primarily by the UIS Grants team. The Principal
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attributes are encouraged to apply: Background in large-scale numerical modeling (regional planning, ecological, hydrologic climatic, or wildfire modeling). Experience with scientific software development in C
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research management and other data analysis software. Application Materials Apply online at https://hr.missouri.edu/job-openings , Job ID 58392. Please submit a single PDF file that includes 1) a cover
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skills and demonstrated record of peer-reviewed journal publications. • Experience managing or coordinating research workflows involving multiple software tools, datasets, or modeling and experimental
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CIIMAR - Interdisciplinary Center of Marine and Environmental Research - Uporto | Portugal | 24 days ago
techniques; - Experience with assay validation and statistical treatment of data (e.g., proficiency with software such as GraphPad Prism, OriginLab, or R); - Experience with electroanalytical methods
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data issues. Utilizing machine learning techniques as appropriate for data analysis. Developing computing programs and software to support research initiatives. Applying new methodologies to real-world
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with data acquisition and analysis using software such as MATLAB or Python. Excellent written and oral communication skills, with a proven track record of publishing research findings. Ability to work
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computation and fusion, systems and software, or modeling multi-layer networks, and active participation in research projects and leading a group of highly motivated Ph.D. students is desired. Urban
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, manage research data and software, and assist in mentoring graduate and undergraduate students. HOW TO APPLY Applications should contain a cover letter briefly describing the candidate's research
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of peer-reviewed publications and conference presentations in traumatic stress. Advanced data anaylsis skills, including use of statistical software (e.g. SPSS, R, SAS). Prior involvement in successful