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Field
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INESC TEC is accepting applications to award 4 Scientific Research Grant - NEXUS - CTM (AE2025-0564)
; - survey and analyze the state of the art in emerging wireless networks, including simulation aspects; - collaborate in the preparation of technical reports on the algorithms, mechanisms, models
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. Expect close collaboration with industrial experts and the opportunity to see your algorithms influence aerospace and other high-value manufacturing sectors. Funding and eligibility 3-year, full-time PhD
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. Expect close collaboration with industrial experts and the opportunity to see your algorithms influence aerospace and other high-value manufacturing sectors. Funding and eligibility 3-year, full-time PhD
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of elements) of the model.; 3) develop an optimization algorithm based on genetic algorithms and metamodels and 4) design functionally graded OC scaffolds using different biomaterials. The doctoral candidate
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interpreted by regression and tree-based machine learning algorithms to obtain even better mutants and develop mechanistic hypotheses. Various collaborations with ON-TRACT network partners across Europe allow a
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, their achievements and productivity to the success of the whole institution. The Faculty of Computer Science, Institute of Theoretical Computer Science, the Chair of Algorithms offers a position as Research Associate
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environments like health care and environmental monitoring. This PhD project aims to address these challenges by exploring how evolutionary algorithms and reinforcement learning (RL) techniques can be combined
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integral methods, stochastic modelling, optimisation algorithms, or numerical simulation. Candidates with interest in electromagnetic theory, quantum mathematics, wave chaos and complexity, as
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management of microgrids, battery scheduling, and handling uncertain renewable generation without relying on forecasted data [1]-[5]. Studies reveal that parametric tuning of RL algorithms such as state and
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environments like health care and environmental monitoring. This PhD project aims to address these challenges by exploring how evolutionary algorithms and reinforcement learning (RL) techniques can be combined