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requirements: Experience using deep-learning algorithms. In-depth knowledge of Python and PyTorch. Previous experience collaborating on scientific projects. Publications on deep-learning topics. 4. Work Plan
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to provide the supporting documents by the grant contracting stage. 3. Preferential Factors Proven experience with decision support systems based on knowledge bases and machine learning. 4. Work Plan The work
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be duly proven at the time of hiring. 2; 3. Preferred requirements: Experience using Machine Learning algorithms. In-depth knowledge of Python and PyTorch. Previous experience collaborating
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the interview are as follows: a) Technical and scientific knowledge in the areas of research at CICS.NOVa.UÉvora in which the scholarship is available (50%): 1. No knowledge – 0 2. Reasonable knowledge – 50 3
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to the following weights and criteria: - Criterion 1 - Motivation and interest (30%) - Criterion 2 – Knowledge and profile appropriate to the functions to be developed (40%) - Criterion 3 - Ability to express
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according to the following weights and criteria: - Criterion 1 – Absolute merit of curriculum vitae - Criterion 2 – Academic background - Criterion 3 – Specific knowledge related to the work plan Skills
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CIIMAR - Interdisciplinary Center of Marine and Environmental Research - Uporto | Portugal | 4 days ago
two years in that type of grant, whether consecutive or intermittent. Candidates are expected to have scientific and technical knowledge on the following eliminatory parameters: Genomic DNA extraction
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or related field;* Solid knowledge in machine vision and deep learning (e.g., TensorFlow, PyTorch, OpenCV); Experience in Python programming (focus on libraries for data analysis and AI); Previous
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and master's theses. Master's degree in law or final-year law student with excellent academic results (cum laude or higher). Good knowledge of Dutch, French and English. You have a demonstrable interest
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to mandatory enrolment and attendance in a degree-awarding third-cycle course; Interest in applied research in the fields of sport and social sciences; Basic knowledge of statistics and SPSS software, as