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these cells mature to generate functional circuits, and how their defects drive neurodevelopmental and degenerative diseases. To this end, our work combines various interdisciplinary techniques such as mouse
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understand the conditions required to ensure the sustainable management of lithium-ion batteries when they reach the end of their useful life in electric vehicles. This will enhance the overall efficiency
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to: rhizosphere and phyllosphere microbiology microbial evolution molecular and/or structural aspects of plant-microbe or plant-fungal interactions the molecular biology of soil-dwelling bacteria or fungi
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contract, individuals may also be supported to apply for PhD funding for a different role to commence at the end of the CRF contract. *This is a 1-year post to gain clinical experience in HPB oncology and to
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., somatic) somatic mutations in the human brain. The lab is interested in studying somatic variation as it pertains to typical brain development as well as in neurological diseases like epilepsy. To that end
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Academic Fellowship scheme for 20 outstanding researchers focused on AI development and application across all disciplines, including health & biosciences, humanities, social & behavioural sciences, physical
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• Receive mentorship in the development of research strategy, scientific writing and networking skills. • Develop and submit longer-term Fellowship applications to major funders. Applicants for a Quadram
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experience in a number of the aspects is required. The role will also offer the opportunity to contribute to the development of research strategies within the group as well as cosupervise masters students in
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risk assessment and informing next-generation regulatory frameworks to better protect human health and the environment from toxic substances. Specifically, the post holder will develop, implement, and
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leveraged to accelerate learning from both classical and quantum data. The project will develop rigorous theoretical frameworks to understand key properties of quantum machine learning models—expressivity