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Dalhousie University | Halifax Mid Harbour Nova Scotia Provincial Government, Nova Scotia | Canada | about 6 hours ago
other project resources. Experience with both qualitative and quantitative data collection. Experience using qualitative (e.g., NVivo or Dedoose) and quantitative analytic software (e.g., Stata or R
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powered by: Cookie Information Nettsiden bruker cookies Vi ønsker at du skal være trygg når du bruker dette nettstedet. Vi benytter cookies for å sikre at du får en best mulig brukeropplevelse og
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data, log-trace data from learning platforms, and panel data. Relevant areas of expertise include longitudinal data analysis, psychometrics, learning analytics, and machine learning. We are particularly
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, Medicare and/or commercial claims data, a deep understanding of analytical methods and statistics, and advanced programming skills are therefore desired. The role will also involve preparation of graphical
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, the project seeks to enhance selectivity, reduce energy consumption, and lower overall system costs for scalable and sustainable REE recovery. Requirements: Education PhD in Chemical Engineering, Materials
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find more information for applicants . Remuneration for the position of PhD Fellow is in accordance with the State salary scale code 1017. A compulsory contribution of 2 % to the Norwegian Public Service
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, tackling real-world data challenges! PhD Research Fellow in Trustworthy Machine Learning Apply for this job See advertisement About the position We invite applications for position as PhD Research Fellow in
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. Criteria of the candidate: To be considered for this position, candidates should meet the following criteria: Recent PhD: Hold a Ph.D. earned within the last five years in Microbiology, Bioprocess
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bank transfer. Eligibility criteria Candidates must be enrolled in a PhD degree/programme in electrical and computer engineering, informatics and telecommunications engineering, or equivalent
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during the employment period. Qualification requirements The successfull candidate must have: a PhD in law, the PhD thesis must have been submitted for evaluation within the application deadline