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methods and data-driven modelling techniques, the PhD candidate will investigate novel frameworks to accelerate SRS in HPC environments. The PhD candidate will work at the Ship Hydrodynamics section
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in ports are attributed to the port call process of ships visiting the port. Efforts of a single actor to reduce emissions will be suboptimal, or may even be counterproductive, for the port call
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PhD Position on Machine Learning Detection of Positive Tipping Points in the Clean Energy Transition
Positive tipping points in the innovation and diffusion of clean energy technologies can greatly accelerate progress towards a net-zero energy system. Yet, their emergence and timing remain difficult
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-of-life PV modules. Thus, research into PV modules designed for cricularity is needed. Research questions/aims: In this project, we aim to accelerate the development of novel liquid-filled circular PV
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PhD Position on Machine Learning Detection of Positive Tipping Points in the Clean Energy Transition
in the innovation and diffusion of clean energy technologies can greatly accelerate progress towards a net-zero energy system. Yet, their emergence and timing remain difficult to anticipate and manage
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address: vacancies-pe-eemcs@utwente.nl) The first round of interviews will be planned early December 2025. Screening is part of the selection process. About the department The Power Electronics (PE) group
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characteristics. Moreover, EN measures passively and continuously, making it very suitable for permanent monitoring or as an accelerated testing method. The effectiveness of EN depends on effective data analysis
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on construction and performance indicators. This will require an insight into how to fully automate the discrete topology design synthesis process across system levels and how to learn component descriptions and
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Join TU Delft and work together with NXP to build low-power AI accelerators for self-healing analog/RF calibration, fixing noise/offset. Co-design algorithms & hardware and validate on real silicon
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strategies to this end. Information This research project is part of the EmPowerED project, which aims to accelerate and scale up the development of Positive Energy Districts (PEDs). PEDs are urban areas