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methods for allocating scarce physical space and time slots among these competing functions across fluctuating daily demand: building demand scenarios from stakeholder interviews, questionnaires, and travel
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of the following: electronic packaging, heterogeneous integration, thermal management, reliability, multi-physics and multiscale simulation. Demonstrated publication record in high-quality
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are preconditions to make a meaningful contribution to the future of sustainable healthcare. Full-time, 36-month postdoctoral position Excellent mentorship and a stimulating international research environment with
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pending) which will build and expand this work. Through this postdoc, we aim to develop approaches for developing awareness and engagement with ELSA across ‘use cases’ (UCs) which are specific, real-world
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(adaptive) imaging strategies and reconstruction. The research combines ultrasound physics, signal processing, machine learning, computational imaging, and clinical translation. Beyond your individual
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, navigation and control, visual landing and event-based vision, scientific deep learning for physical systems, spiking neural networks for event-based systems. Building on this experience, the research line
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fair recruitment process that does not rely purely on common research metrics. The successful applicant will have: A PhD in Materials Science, Applied Physics, Electrical Engineering, Chemistry or a
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science, atmospheric chemistry, environmental science, aerosol science, physics, environmental engineering or a closely related discipline. Demonstrated expertise in atmospheric chemistry, aerosol science
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Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description Hey machine learning enthusiast with a love for physics and
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. parental leave, caring duties, part-time jobs to support studies, disabilities etc.) to ensure an inclusive and fair recruitment process that does not rely purely on common research metrics. The successful