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- Nova School of Business and Economics
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- Universidade Lusófona´s Research Center for Digital Human-Environment Interaction Lab
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able to prepare written reports and work with spreadsheets and statistics programs. Good knowledge of the English language in oral, reading and writing terms. Work Plan: Bibliographic research to select
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work in a team. Be able to prepare written reports and work with spreadsheets and statistics programs. Good knowledge of the English language in oral, reading and writing terms. Work Plan: Optimization
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for characterization of cells (flow cytometry, metabolism, immunofluorescence microscopy); 4)Microscopy image analysis; 5) Data analysis using statistical tools. Proficient use of the English language, both spoken and
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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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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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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
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WORK PLAN: ………………………………………………………………….……………………….. · Database cleaning and organizing · Initial statistical treatment and regression analysis · Support in the writing of articles
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, collect and analyze urban transport data, and test and develop statistical models to predict transport demand and flows. These models should be applied to real case studies. Legislation and Regulations
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at source and operations related to discounts on compensation; c) Conducting non-nominative statistical operations related to the processing of salaries within the processing entity. 3. The entities referred