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Requisition Id 16736 Overview: We are seeking a Postdoctoral Research Associate who will work with a multi-disciplinary group of experts in economics, engineering, software development, and building
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, including the application of advanced statistical methods such as survival analysis and longitudinal data analysis. Proficiency in statistical programming and data management using software such as SAS, R
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with process simulation software such as Aspen Plus or Aspen HYSYS Application and Selection: The application folder must contain: Detailed CV, Cover letter along with a synthetic presentation of the
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to development of open-source software. Receive tailored mentorship in grant writing (e.g., NIH K99/R00), career planning, and leadership. Minimum Qualifications: The candidate should hold a Ph.D. (or equivalent
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for developing and refining scientific protocols, overseeing data collection and analysis using advanced statistical software (e.g., SPSS, STATA, R), and ensuring compliance with international standards. He/She
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Austrian Academy of Sciences, The Marietta Blau Institute for Particle Physics (MBI) | Austria | 2 months ago
) Software skills for experiment control (LabView, Python), simulation (SIMION, Comsol/CST, Geant4) and data analysis (Python, C++). Desirable Skills: Knowledge of the following topics: Trapped charged
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research profile focuses on development of novel statistical methods and software for the analysis of large and complex data sets. Applications include e.g., evaluation of large-scale achievement tests, and
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Post-doctoral Fellow / Senior Research Assistant (Holding the Functional Title of Senior Psychology)
and spoken English and Chinese. Strong research skills in Psychology or Social Sciences. Proficiency in statistical software (e.g., SPSS, Jamovi, or R), as well as MS Excel and Chinese typing
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participatory workshops; Processing, analyzing, and interpreting collected data (transcriptions, data processing with analysis software, etc.); Writing academic texts derived from the project: scientific articles
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ecosystems, forested wetlands, or peatlands. ● Demonstrated proficiency with statistical computing (e.g., R, Python) and spatial analysis software (e.g., ArcGIS, QGIS). ● Experience with carbon stock