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data is often affected by significant noise and scan distortions. High-quality ground truth data is usually unavailable or costly to collect. To overcome this, we focus on self-supervised denoising
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other departmental duties, up to a maximum of 20 per cent of full-time. A high level of presence at your workplace is expected so that you will be able to benefit and contribute to the lively
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-responsive and multi-modal operation. The tasks will include: Exploring new doping strategies to modulate the properties of organic semiconductors Performing optical/electrical measurements to study charge
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. Our aim is to engage in medical and biomedical education and research of high international standing. At undergraduate level the department is responsible for most of the medical program, the speech and
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functionalities. The research aims to expand the capabilities of organic electronic devices by integrating light-responsive and multi-modal operation. The tasks will include: Exploring new doping strategies
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applications towards materials science. Generative machine learning models have emerged as a prominent approach to AI, with impressive performance in many application domains, including materials discovery
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original, high-quality research in trustworthy machine learning. You are expected to: Publish your findings in leading journals and conferences. Present your work to both academic and industry audiences
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prominent approach to AI, with impressive performance in many application domains, including materials discovery. This development has a huge potential for societal impact, with applications in renewable
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strategies that balance the tradeoff between privacy and utility in continual, federated, and distributed settings. Your primary responsibility will be to conduct original, high-quality research in trustworthy
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to largely contribute to improved environmental performance of the built environment but many challenges remain, particularly related to data sharing between actors in the supply chain. This project will study