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to the high-temperature PEMFC to produce warm water for practical applications (e.g., heating and washing) in disaster areas. Investigate the thermal dynamics and overall performance of the HT-PEMFC stack and system under
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Job Description You will join a supportive and dynamic research team working at the intersection of machine learning and operations research. Your main task will be to design and implement ML
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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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than RGB will be actively researched. Exploring 3D canopy modelling and plant growth dynamics for digital twin integration. Self-supervised learning will generate multi-modal agricultural pre-trained AI
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for sustainable production of food by applying your microengineering and material science skills? Here, we can offer you a unique opportunity to do exactly that in a dynamic research environment. In the SOLARSPOON
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to work independently within a dynamic research environment Willingness to collaborate with other research groups Excellent skills in written and spoken English You should strive for scientific excellence
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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
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special focus on the possibilities offered by dynamically controlled cavities and extreme light confinement. You will have the opportunity to co-supervise BSc and MSc students. The project is funded by
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Doctoral School of IT and Design Further information We 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