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. Collection, integration and analysis of data from various sources (e.g. clinical, biochemical); 2. Databases creation and update, and application of statistical methods for analyses; 3. Performing functional
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, Centro 2030. The grant is intended for students enrolled in non-degree courses or PhD students in the field of Chemical Engineering or related areas, holding a Master's degree in Chemical Engineering or
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Associação do Instituto Superior Técnico para a Investigação e Desenvolvimento _IST-ID | Portugal | 4 days ago
and cast parameter/state/fractional‑order learning as an Expectation–Maximization (EM) procedure interpreted through a dynamical‑systems lens (e.g., fixed‑point/stability analysis of the EM iterates
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enrolled in a PhD program - art. 6º, c) https://diariodarepublica.pt/dr/detalhe/regulamento/950-2019-127238533 https://files.dre.pt/2s/2019/12/241000000/0009100105.pdf subject to suitable performance within
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TEC. 2. OBJECTIVES: Collaborate with clinical partners in data collection and annotation Design and implement new deep learning solutions for the analysis of heart sound auscultation, electrocardiogram
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AND EVALUATION CRITERIA: The evaluation will be based on the curricular analysis and will focus on candidate merits, which will be considered and weighted according to the following: a) Suitability of
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of the key performance indicators defined by the WP1 teams; and 3) developing applications for visualization and analysis of data and metadata. 6. Legislation and regulations: The fellowship assignment will be
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. • No knowledge – 0 points. Final grade (FG) = [AQ*0.5 + PAE*0.2 + SK*0.3] If the jury decides by reasoned deliberation, the three first classified in the curriculum analysis will be invited for an interview (INT
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microgravity environments. The fellow will have the opportunity to acquire skills in research applied to space technology, combining theoretical analysis, simulation, and experimental validation. 4. REQUIRED
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/pagamento-propinas-bolseirosEN ) The grant holder will benefit from health insurance, supported by INESC TEC. 2. OBJECTIVES: Real-time signal analysis algorithms, feature identification, and personalized