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related to e-mobility (e.g., distributed generation, storage, electric vehicles, smart energy management systems, etc.) and how to design the right incentives for a welfare-maximizing e-mobility integration
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to the collected dataset. Deep learning will focus on physics-based features developed earlier. Convolutional layers will be used to extract spatial patterns, while LSTM layers will capture temporal aspects across
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the immune response to mpox in both animal models and in vitro systems. We are looking for a motivated PhD student to help advance this line of research. As a PhD student, you will: Design and conduct
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of migrant communities in Belgium, focussing on mobility patterns (internal migration), family transitions and mortality using administrative datasets. The findings will be published in scientific journals and
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live in. Your role The PhD candidate will generate and study complex macroscopic flow patterns of LCE precursors, polymerize the precursors into LCEs programmed by the flow patterns, and study the
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hydrogen storage tanks. This PhD vacancy is focused on the finite element modelling and design of the pressurized composite tank, in different operational conditions (static burst, fatigue and impact). The
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., qualitative, quantitative, design science research) will be considered an asset A collaborative team player with a desire to make a personal impact within our interdisciplinary research group The commitment
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X-ray videocystometry in awake mice. The candidate will design and conduct experiments exploring the signalling interactions between urothelial cells and sensory nerves innervating the bladder, and
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advanced techniques such as ex vivo calcium imaging and transcriptomics of mouse and human urothelium and DRG neurons, and X-ray videocystometry in awake mice. The candidate will design and conduct
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also a pioneer in in situ 3D ED studies, as will be important in this project. More about us at our webpage . Position You will design and fabricate lithographically etched sample supports and MEMS