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parameters using experimental muscle and neural recordings Explore motor control policies that replicate observed behaviours Test simulation predictions against muscle ablation experiments Investigate how
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Instituto de Investigação e Inovação em Saúde da Universidade do Porto (i3S) | Portugal | about 6 hours ago
‘centromeric’ view on ageing by: i) characterizing age-associated changes in centromere features in cellular models; ii) identifying the intrinsic (genetic and epigenetic) and extrinsic (viral infection
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open to candidates with a strong interest in either: i) Radio/physical-layer intelligence (e.g., channel estimation, CSI prediction, edge-deployable deep learning), or ii) Networking and control-plane
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. The work is part of the regional project “Optimizing Renewable Energy Integration: FPGA-Based Model Predictive Control (MPC) for Grid Stability” (Ref. SI4/PJI/2024-00238) Where to apply Website https
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incorporate clinical, lifestyle, and nutritional factors to build predictive models through advanced bioinformatics and machine learning. By identifying molecular signatures that distinguish responders from non
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project involves interdisciplinary research at the interface of computer science and mathematics, with a focus on bivariate molecular machine learning for modeling molecular interactions and properties
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Learning-enabled control and reinforcement learning Power system operations, planning, and electricity market design Transportation systems modeling and optimization Responsibilities: Postdoctoral fellows
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review, Asana and JIRA for agile project management, and Qlik Cloud, Snowflake and Posit Connect for deploying dashboards and predictive models to support the University’s sophisticated fundraising
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on advancing Predictive, Preventive, Personalized, and Participatory (P4) approaches in health and medicine. Within the IRAP framework, the project’s scientific goal is to discover and validate novel therapeutic
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identification, i.e. learning of models from measured data, and iii) real-time control, e.g. using the model predictive approach. We are working on several projects with industrial partners across the energy