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models, real-time telemetry, and AI-enhanced analytics, the research aims to enable continuous simulation and verification across the entire ECU lifecycle—from early model-in-the-loop design to deployment
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, necessitating advanced modeling and simulation techniques to analyze and address these issues. Research field: Production and materials engineering, robotics, transport and logistics Offered by: School
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highly motivated and ambitious PhD candidate with experience in either biomedical engineering, machine learning, polymer technology, physics, electrospinning, or similar fields,to join our Lab- on-a-chip
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within a Research Infrastructure? No Offer Description We are looking for a highly motivated and ambitious PhD candidate with experience in either biomedical engineering, machine learning, polymer
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scenarios. Designing validation metrics for coverage, criticality, and novelty. Integrating LLM-based testing into simulation platforms (CARLA, SVL) and open-source stacks (Autoware). Applying validation
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-processed functional materials Use of AI/ML and numerical simulation to optimize the microstructure-properties in the functional materials fabricated by the LPBF process Optimization of microstructure and
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involving both theoretical and practical aspects of perception systems, with the potential to generate publications in high-ranked journals and conferences using both simulations and robotic vehicles
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topologies tailored for DC-powered HVAC units Synthesis and implementation of control strategies enabling droop-based HVAC operation with optimized energy efficiency Implementation of simulation models (PLECS
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expected contributions. Copy of the identification page of your passport or official Estonian identification document Foreign applicants must submit proof of English language proficiency, which must be
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for the novel permanent magnet-assisted reluctance machine could help to improve existing control strategies. Real-time simulations Design control algorithms, vision, or plant models in MATLAB/SIMULINK Build a