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Field
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contact with the practice of medical law and cultivate relevant networks. This is part of your personality: Completed doctoral/PhD studies in law with a focus on Austrian medical law Outstanding
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state-of-the-art machine learning and deep learning techniques (such as generative adversarial networks), with empirical fieldwork in Norwegian glacier environments. As a Postdoctoral researcher, you will
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Computational Neuroscience and related fields as part of the Medical Research Council, UKRI grant “Algebraic topology bridging the gap between single neurons and networks”. They will be expected to conduct
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publish them in high-impact journals. In addition to research, you will also be expected to take part in the supervision of PhD students and the teaching activities of the research group. Your network and
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expertise in controlling and deploying them in practice, as well as in designing coordination strategies for them. Our recent work on RL and graph neural networks (GNNs) demonstrate some of our key research
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of early tissue responses in vaccination with mRNA vaccines (MechRNA) as part of the larger the Lymph nodE single-cell Genomics AnCestrY and ageing (LEGACY) Network. This project involves profiling the intra
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tissue responses in vaccination with mRNA vaccines (MechRNA) as part of the larger the Lymph nodE single-cell Genomics AnCestrY and ageing (LEGACY) Network. This project involves profiling the intra-lymph
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leader Pedro G. Ferreira and other members of the Beecroft Institute of Particle Astrophysics and Cosmology. The post holder will be a member of a disparate research network working independently to carry
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datasets for the ML tool, which will be based on a Tensorial Neural Network architecture, will be provided by Molecular Dynamics simulations also conducted in E-COOL. Person Specification The successful
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, green business, decision support. Understanding of the net zero and/or circular economy. Research Excellence Proven strong track record of high-quality publications. Ability to work independently and