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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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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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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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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
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partners. The candidate will have the opportunity to work with state-of-the-art tools for simulation and design power converter and electric machine and control the converter with advanced power electronic
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. Experience with quantum simulators, such as NetSquid, is a plus; Familiarity with the basic concepts of quantum information and quantum computing; Curiosity to research and develop new solutions in
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, a certified/signed copy of a recent transcript of records or a written statement from the institution or supervisor is accepted. Publication list (if possible) Reference letters (if available
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CMOS circuits with real or simulated qubit systems. Understand the specific requirements and constraints of interfacing with qubits (control fidelity, noise sensitivity, power dissipation, etc
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: Motivated cover letter Special PhD application form (available here ) Curriculum vitae Bachelor's and Master’s degrees or equivalent (copy of original + verified English translation) A complete list of
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with regular waves. 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