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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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, and an application must include: Motivated application. Curriculum Vitae. Master’s and bachelor’s degree certificates or equivalent, including transcripts of grades (copy of original/official English
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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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documents in PDF format: 1. Motivated letter of application (max. one page) 2. CV incl. education, experience, language skills and other skills relevant for the position 3. Certified copy of original Master
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project description. Please simply copy the project description above and upload it as a PDF in the application. Qualifications and specific competences Applicants to the PhD position must have a relevant
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proficiency in relevant programming languages (e.g., Python, C++) and tools such as ROS. Experience in simulation and digital twins, as well as the use of synthetic data for training machine learning models, is
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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