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excellent proficiency in English. EVALUATION CRITERIA The selection will be based on the following criteria: CV (30%) Motivation letter (20%) Speech processing (20%) Binarized nnets/crypto (20%) Voice
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to mitigate the risk of triggering anti-scraping mechanisms. To achieve this, the student will first establish a base deployment system for running the generated scrapers and storing their collected data and
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, specifically in problems related to clinical natural language processing. Self-motivated and showing initiative in solving problems. EVALUATION CRITERIA The selection will be based on the following criteria
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programming proficiency EVALUATION CRITERIA The selection will be based on the following criteria: 75% - Candidates will be assessed by CV evaluation taking into consideration the above preferential factors
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The selection will be based on the following criteria: Academic Curriculum (50%)Previous experience (50%) The evaluation panel assigns a classification to each of the candidates on a scale of 0 to 100 points
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CRITERIA The selection will be based on the following criteria: 50% - Experience in the domain of the project (academic activities or projects in the scope of programs addressing state of the art and
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and Data Science - Previous experience in Data Analysis and Integration, and in Information Visualization is a plus EVALUATION CRITERIA The selection will be based on the following criteria: 70% - CV 30
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systems where the candidate played an active role together with familiarity with deep learning methods. EVALUATION CRITERIA The selection will be based on the following criteria: CV: 50% Experience in