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short- and long-term demand prediction, renewable generation forecasting (solar, wind, hydro) under uncertainty, spatiotemporal modeling for distributed energy systems, energy markets, transfer learning
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development of model predictive control algorithms for autonomous robots. Key Responsibilities: Development of model predictive control algorithms for autonomous robots Job Requirements: A Master degree in
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or comparable analytics tools Proficient in data mining, visualization, and machine learning skills Understanding of predictive modeling, NLP, and machine learning Excellent organizational and time-management
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interest in social science applications, and with strong competence in statistics and machine learning. The successful candidate will develop predictive models using machine learning and work alongside other
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, computational pathology, and spatially resolved multi-omics data. The system will leverage generative models like diffusion models and Variational Autoencoders (VAEs) to simulate phenomena and predict outcomes. A
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deep learning models to predict and analyze large-scale orbital capability. - Evaluate and optimize the performance of the models, comparing them with traditional orbital analysis methods. Where to apply
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-the-loop control for extreme robotics applications, including high performance algorithms for 3D perception, model predictive control, reinforcement learning, generative AI, and simulation and virtual
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environment. Development of models to diagnose and predict battery performance and ageing. Participation in national and international research projects related with energy storage and its integration in
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pain, a critical and currently missing component in translational research. These new models are intended to enable accurate prediction of analgesic efficacy and disease-modifying effects of novel
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recover quickly from disruptions. The research will involve reinforcement learning, predictive modeling, and real-time adaptive control to dynamically optimize production sequencing, resource allocation