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) assessing physical activity; (3) preparing and managing the database and its statistical analysis; (4) writing scientific articles. The main grant goals are: a) Define the study sample; b) Organize the data
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ongoing CoLAB projects. h) Analyzing and producing statistical indicators on tourism and hotel activity. Requirements Research FieldManagement sciencesEducation LevelPhD or equivalent
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Participating in the ideation and planning of future projects Skills & Experience: Advanced degree in Computer Science, Engineering, Statistics, or a related field. 2 years of experience in relevant roles Strong
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of experimental results to technical and business stakeholders Skills & Experience: PhD or Masters in Computer Science, Engineering, Statistics, or related field preferred For Masters candidates, 2+ years
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Computer Science, Engineering, Statistics, or related field preferred For Masters candidates, 2+ years of relevant, practical experience Strong foundation in machine learning and statistics Proficiency in Python
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contracts of researchers under a UNL employment contract, Professor Miguel de Castro Simões Ferreira Neto, Dean of the Higher Institute of Statistics and Information Management of the NOVA University
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for Undergraduate Students IMS_BOLSA_BII _2024_01 The Higher Institute of Statistics and Information Management of the Nova University of Lisbon – Information Management School (NOVA IMS) opens a call for the award
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the role, you'll need: 5+ years of hands-on data science experience. In-depth knowledge of AI/ML/DL, Statistics, and related open-source libraries. Awareness of current ML techniques, keen on self
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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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Universidade Lusófona´s Research Center for Digital Human-Environment Interaction Lab | Portugal | 4 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