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Field
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medicine, complex disease mechanism, systems pharmacology, bioinformatics, and network science/statistical physics. This position at Northeastern University may include opportunities to collaborate with
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About the Role The project “An Erlangen Programme for AI” (funded by the UKRI), will broadly involve applying advanced mathematical techniques for understanding training in neural networks, with
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emphasize the different kind or levels, known as layers, of connections between the elements of the network and the interactions between these levels as well. In order to capture the structure and complexity
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processes and stochastic analysis Theoretical analysis of neural networks and deep learning Foundations of reinforcement learning and bandit algorithms Mathematical and algorithmic perspectives on large
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, purification of protein complexes, analysis of protein-protein interactions including electron microscopy, and cellular biology techniques to examine the effects of bacterial membrane vesicles in primary immune
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responsible for the project Design, synthesis, and characterization of complex organic molecules which play a pivotal role in DNP, Employ advanced NMR/MRI methods for structural analysis and DNP-related studies
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public health and clinical service innovation in an increasingly complex and connected world. The selected candidate will join a research project and assist the Principal Investigator. The responsibilities
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learning techniques to address complex biological questions with significant societal impact. The position offers the opportunity to contribute to groundbreaking research that will advance our understanding
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/functional inequalities Markov processes and stochastic analysis Theoretical analysis of neural networks and deep learning Foundations of reinforcement learning and bandit algorithms Mathematical and
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Australian National University | Canberra, Australian Capital Territory | Australia | about 8 hours ago
university Advance transdisciplinary scholarship through research, collaboration and high-impact practice Engage with regional communities in the development of community-led flood intelligence networks