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(EMG), to capture detailed motion, interaction forces, and muscle activity. Predictive Physiological Modeling: Development of machine learning models capable of anticipating motion intent while
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Foundation-model-guided world models and predictive control for autonomous remote handling in extreme environments The Fusion Engineering Centre for Doctoral Training (CDT) PhD Research Project
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, vol. 167, p. 115644, Mar. 2025. https://doi.org/10.1016/j.microrel.2025.115644 [2] A. Bender, “A Multi-Model-Particle Filtering-Based Prognostic Approach to Consider Uncertainties in RUL Predictions
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documents uploaded using the dedicated electronic form. helpdesk: petra.koudelova@fsv.cvut.cz High-Velocity Dust Impacts on Tungsten Plasma-Facing Materials: A Predictive Multi-Scale Modeling Framework with
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systems capable of selecting and combining models of different complexity, in order to better represent groundwater dynamics and improve large-scale predictions under climate change. Objective — The PhD
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methodologies for modeling and predicting the properties of complex materials and surfaces, including doping and/or functionalization to optimize their physicochemical characteristics Where to apply Website http
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state‑of‑the‑art structure prediction and design frameworks, training/fine‑tuning models, and running scalable computational campaigns. Key responsibilities Design and execute in silico protein and
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unit dedicated to advancing the understanding, monitoring, and predictive modelling of modern engineering structures. Research within the department on Structural Health Monitoring (SHM), non-destructive
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charging) Predictive charging planning algorithms Railway Smart Pricing models Techno-economic evaluation versus the traditional catenary model This is applied research with validation in simulated
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frontiers in oenology, central to the development and management of sustainable oenological practices. This project aims to develop predictive models of longevity and shelf-life based on easily acquired