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systems to operate safely and efficiently. Possible research directions include advanced flight control, model predictive control, nonlinear control, fault-tolerant control, cooperative control and aerial
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research, digital health solutions, and the development of AI-based predictive models using large-scale clinical datasets. This position is particularly suited to a clinician-scientist with a strong
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the provisions of the Decree-Law no. 66/2018, of august 16th, and any formalities established there must be fulfilled until the time of signing the contract. Activity Outline: Development of control strategies
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and requires a hybrid work schedule that includes 1-2 days working in the office Monday-Friday during regular day shift hours. Regular and predictable attendance is required. Key Responsibilities
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predictive algorithm of School-age neuropsychological outcome will be developed combining radiomic model of brain development, with qualitative neonatal MRI findings. Achievement of the expected progression
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learning, understand their mathematical foundations, and connect them to space-related technologies and missions. The focus is on building rigorous models that explain and predict the behaviour of modern
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(PAPROG) with the overarching goal to develop an operational modeling tool for glacier hazard prediction and analysis. This PhD will benefit from technical support funded by the project and collaborations
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between pollution control efficiency, electrochemical yield, and energy recovery potential; • Develop coupled electrochemical and hydrodynamic models to predict process behavior; • Participate in
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patients develop a durable response. Many researchers are investing efforts to understand the complexity of anti-cancer immunity and develop diagnostic approaches that accurately predict therapy benefit and
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unexplored. Conversely, models predicting future Arctic primary production often assume poleward shift of species based on thermal optima, without accounting for the adaptive capacity of local populations