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trustworthy AI and seeks to produce ground-breaking results that have been tested on real-world problems. In advancing trustworthy AI, TRUST will develop new AI technologies, support innovation, and investigate
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research into power electronics for energy management and decarbonization. Vision We are seeking a PhD student that is motivated and passionate about the design and control of power electronics technologies
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Heidelberg Institute for Theoretical Studies (HITS gGmbH) | Heidelberg, Baden W rttemberg | Germany | about 8 hours ago
for crystalline materials, such as diffusion models and flow matching. Future applications of this technology include the design of novel materials for batteries and catalysts for direct carbon air capture. Your
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. It will require co-design of survey instruments incorporating stated choice experiments and the application of experimental design principles to ensure that the survey delivers high quality data
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motor processes. Each project will be designed with our steering group of people with a diagnosis of Parkinson’s. Candidates with a background in neuroscience, clinical sciences or related discipline are
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education, research, and innovation, which has been inspiring generations of thinkers for over 400 years. This fully funded PhD studentship is part of a larger interdisciplinary project, Implementing and
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desirable but not essential. Durham University is a leading Russell Group institution in a historic North East England city with excellent quality of life. Intel leads in computing innovation for efficient
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University’s Faculty of Geosciences studies the Earth: from the Earth’s core to its surface, including man’s spatial and material utilisation of the Earth – always with a focus on sustainability and innovation
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smouldering offers a promising solution to reduce the amount of material destined for the GDF: it is energy‑efficient, cost‑effective, and well‑suited to low‑volatility carbon‑based materials. You will design
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physics-based and data-driven methods to support the design and scale-up of these systems. This approach will reduce the need for costly experiments, improve scale-up predictions, and provide confidence