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Field
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chemical production, the focus is on optimizing yield, distribution, or conversion by testing different operating conditions (pressure, concentration, temperature, etc.) and at isothermal conditions. Then
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project, you will help design, simulate, and optimize these next-generation communities — making clean, local, and intelligent energy systems a practical reality. Your key responsibilities include
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3.5-year D.Phil. studentship Project: Optimization for real-time electricity grid operations Supervisor: Jack Umenberger This project concerns real-time balancing of energy in the electricity grid
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and how these intersect, their labour cost rates will be calculated. These calculations, based on optimal socio-economic work patterns, and on pre-industrial agricultural subsistence activities, will
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machine learning to generate more accurate demand and supply predictions, which will then be used in the optimization process. The project will also investigate the strategic use of real-time sensor inputs
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—of linguistics, psychology, computer science, philosophy, education, and neuroscience. The doctoral student's work will be part of the Language and Cognitive Processes team, whose research focuses
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genetics to predict breast cancer risk and tumour aggressiveness in BRCA variant carriers Digital biomarkers for enhanced AI-guided therapy in heart failure (D-BEAT) Experimental models for optimizing
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tracking and mapping, light fields, extended reality (XR) technologies, sim-to-real, synthetic data generation, and advanced computer vision and machine learning techniques. In addition, the group works on
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such as surgery, patient or staff scheduling using, e.g., multi-objective optimization or machine learning approaches and analyzing efficiency-fairness trade offs. The research will be conducted under
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SELECTION PROCEDURE FOR THE RECRUITMENT OF AN INITIAL-LEVEL DOCTORAL RESEARCHER ON A PRIVATE LAW EMPLOYMENT CONTRACT WITH INDEFINITE RESOLUTION CLAUSE AT THE FACULTY OF MEDICINE OF THE UNIVERSITY OF PORTO (Pr