15 computational-physics-simulation PhD positions at University of Southern Denmark in Denmark
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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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results with AI models and system simulations to create a digital twin of the PtX process for predictive optimization and scenario analysis. Funding This PhD position is generously funded through the Villum
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The scholarship is a collaborative effort focusing on industrial design and optimisation of product assembly, quality inspection, and assembly process optimisation. It is expected to be a cross-disciplinary
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group at CIE. The aim of the position is to build strong knowledge and competencies within the field of electrochemical storage device design, simulation and testing. Job description You will conduct
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contact information • Certified copy of diploma (Master’s degree in a relevant field) Shortlisting may be used in the assessment process. Further information about the PhD-study can be found at the homepage
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, for static and dynamic measurements and reliability measurements). Key Responsibilities Research & Learning: Develop expertise in GaN device physics and wide-bandgap semiconductor technology. Simulation
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• Certified copy of diploma or expected date of graduation (Master’s degree in a relevant field) Shortlisting may be used in the assessment process. Further information about the PhD-study can be found
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to perform an experimental PhD in Physics in the area of Quantum optoelectronics and 2D materials. The position is available from 1 October 2025 or as soon as possible thereafter. The successful candidate will
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the value of the green transition. The project will involve a multi-stakeholder innovation process, utilizing a framework of multiple-loop learning to encourage farmers to reflect on their relationship with