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with information on participants; . transcription and coding of linguistic data (resulting from experimental tasks or from spontaneous data collection); . preparation of databases for statistical
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techniques for environmental sciences – information provided in the CV and/or motivation letter; e) Experience in statistical analysis, preferably in an R environment – information provided in the CV and/or
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Associação do Instituto Superior Técnico para a Investigação e Desenvolvimento _IST-ID | Portugal | about 1 month ago
tools, statistical models and BIM (30%). The final evaluation results from the sum of the curricular evaluation and the interview evaluation. If none of the candidates has the appropriate profile
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Universidade Lusófona´s Research Center for Digital Human-Environment Interaction Lab | Portugal | 24 days ago
in developmental neuropsychology research methods; d) Fluency of both Portuguese and English languages (spoken and written); e) Fundamental knowledge of statistical software (e.g., SPSS, STATA); f
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. Preference will be given to candidates with previous experience in conducting studies in the field of implicit learning using statistical learning paradigms; Proven expertise in experimental programming (e.g
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, having international publications in peer reviewed journals. The list of publications must be included in the curriculum with a clear indication of the statistical analyses used, along with the candidate’s
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and Experience: Masters in Computer Science, Engineering, Statistics, Economics or related field preferred Ability to write complex SQL queries rack record of leading the deployment and maintenance
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Statistics; Finance; Innovation; International Business and Area Studies; Regional Studies, Planning and Environment. Journal Citation Reports: Business, Finance; Development Studies; Economics; Industrial
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Systems; Software Engineering; Mathematics: Mathematics; Mathematics, Applied; Mathematics, Interdisciplinary Applications; Statistics and Probability. Scimago Journal Rank (Scopus): Computer Science
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Requirements: Master’s degree in economics or in life and health sciences. Enrolled in an academic or non-academic degree-granting course. Experience in data analysis and statistics, demonstrated by a curriculum