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Join the cutting-edge RAM³ project: Unlocking the Potential of Recycled Aluminium through Machine Learning, High-Throughput Microanalysis, and Computational Mechanics. We are offering a PhD position
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the right one for you! This is a fully funded PhD position to develop micromechanical models of high-pressure die-cast aluminium, a unique opportunity for a motivated individual to work in a collaborative
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studies related to the project. The overall goal of the project is to synthesize new energy storage materials, evaluate the properties and develop high performance battery. To achieve the goal, you need
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universities. About the research project This PhD project is part of the interdisciplinary WASP-WISE NEST project RAM³, which aims to enable the use of recycled aluminium in high-performance applications through
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AI training has emerged as the standard approach, which utilizes thousands of high-performance devices within a data center to collaboratively process tasks. When they are even more complex, the
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network. This project aims to develop skills for an autonomous mobile robot to perform complex manipulation tasks. Our goal is to enable continuous learning, allowing the robot to improve over time by
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NEST project RAM³, which aims to enable the use of recycled aluminium in high-performance applications through machine learning, computer vision, and materials science. The focus of this position is on
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Team up with up to 3 fellow Ph.D. students in the DSP-assisted Wideband & Efficient Transceivers (SWEET) project which is part of the WiTECH center to perform cutting-edge multi-disciplinary
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is, however, the transportation and storage. Current methods rely on liquid compressed hydrogen, which requires high pressures or low temperatures. This project will computationally explore catalyst
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high-quality research on interpretable and learning-based stochastic optimal control for over-actuated electric vehicles, with a focus on ensuring robustness and fail-safe operation. You will: - Develop