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design next-generation computer architectures for running large AI models on embedded and edge systems under strict timing, energy, and memory constraints. You’ll explore hardware-aware optimization and co
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embedded in the ThromboRisk framework and includes secondments at partner institutions. Below is an overview of the available positions: Project 1 - Personalized hemodynamic modelling of carotid artery
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allow the inclusion of tumor cells, and the cells should be embedded in a relevant extracellular matrix (ECM); third, the chips must be acoustically transparent to allow transmission of ultrasound, i.e
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that enable efficient problem-solving through energy minimization. In this project, we aim to further explore and exploit the potential of ONNs in embedding graph-based problems, particularly those known to be
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for Predictive Product Properties (MTV)". Your research focuses on the experimental and material-modelling foundations required to enable predictive and controlled TVAM. You will be embedded in the Processing
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-groups/innovation-sciences/human-technology-interaction The position is embedded in TU/e’s strong AI ecosystem and connected to the Eindhoven AI Systems Institute (EAISI) and game research facilities
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researcher, and work with national and international partners. https://www.tue.nl/en/research/research-groups/innovation-sciences/human-technology-interaction The position is embedded in TU/e’s strong AI
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you will be embedded in the Quantum & Terahertz Systems (QTS) team within the Electro-Optical Communications (ECO) group of the Department of Electrical Engineering at TU/e. Within QTS you will work
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. These methods must be embedded in an iterative procedure to compute the final design and are based on Monte-Carlo simulation. They are known to have slow convergence. Using the Hamiltonian structure of the system