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Field
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medical physics, computer science, biomedical engineering, electrical engineering, applied mathematics, or a related field; or an MD with significant research experience and deep familiarity with AI
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Cryptography o Data Sciences, Complex Networks, Mathematical Biology o Quantum Computation & Information Science o Post-Quantum Cryptography, Homomorphic Encryption and Computing o Theoretical and Computational
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perivascular cells of the neurovascular unit/perivascular niche, and on brainvascular heterogeneity in development, health and disease: The main aims are: i) to understand the cellular and molecular
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: □ Computational Sciences o Cryptography o Data Sciences, Complex Networks, Mathematical Biology o Quantum Computation & Information Science o Post-Quantum Cryptography, Homomorphic Encryption and Computing o
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of higher education in the following disciplines including (but may not be limited to) biochemistry, biological sciences, chemistry, computer science, engineering, electronics, materials science, mathematics
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Job Purpose The Clinical PhD Research Fellowships are fixed term 3-year appointments offering training, mentoring and support to health professionals undertaking a PhD on the topic of multimorbidity
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of Computer Science at UiT The Arctic University of Norway. HDL’s mission is to build and experimentally evaluate the systems, methods, and tools needed to analyze and interpret complex health datasets. The group
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position for a Research Associate/Fellow (Data Scientist) in Data Science at the Department of Family Medicine (DFM) within the National University Health System (NUHS). The role is focused on leading data
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. We provide mechanistic, individualized, preventive and multidisciplinary knowledge on a topic that is a global threat to societies: shortened health span and an aging population. Delaying age-related
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Electronic Health Records from people with epilepsy across multiple NHS hospitals in England and Wales. They are expected to have some experience working with NLP in general and LLMs in particular. Familiarity