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to apply machine learning techniques to a combination of experimental data and simulation results, aiming for faster and more accurate predictions. About us You will join an international and highly
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cutting in the production facility. Establish a numerical model to simulate the glass cutting process. Design experimental measurements and assist in the integration of sensors in production. Acquire
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will be conducted 16 - 30 September 2025. Further information We recommend that you save a copy of the job posting, as it will be removed from the website once the application deadline has passed
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Hardware-software co-simulation and benchmarking This PhD project is part of SDU microelectronic unit’s effort in neuromorphic chip design and collaborates with international partners working on spiking AI
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recommend that you save a copy of the job posting, as it will be removed once the application deadline has passed. The assessment of candidates for the position will be carried out by qualified experts
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(28nm or below) Hardware-aware modeling of state-space inference pipelines Simulation and synthesis of the architecture using EDA tools Benchmarking against transformer-based hardware accelerators Work
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. Extending the model to full two-way coupling, allowing feedback from flexible vegetation on wave-induced flow. Applying the fully-coupled model to simulate interactions under both regular and irregular wave
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on developing machine learning algorithms to support the use of complex urban simulators in decision-making under uncertainty. This PhD project shifts the focus from optimality to relevance in urban land-use and
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, satellite altimetry, ice flow maps and terminus positions and other relevant data to constrain numerical model to simulate 1900-present and future (present-2100) ice flow changes under different UN IPCC
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of the power converters in collaboration with our industry partners. The candidate will have the opportunity to work with state-of-the-art tools for simulation and design power converter and advanced power