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Field
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Qualifications Experience with machine learning and AI models. Ability to communicate clearly with colleagues, Data presentations Scientific publication experience Special Instructions Priority Application Review
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volumes, there is a plan to utilize modern machine learning strategies like "physics-informed neural networks." One of the main advantages of this approach is that measurements and observations made
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thrombosis and lung injury in Sickle Cell Disease. The prospective candidate will have the opportunity to learn state-of-the-art techniques such as Multi-Photon-Excitation intravital microscopy of the lung and
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use of molecular assays such as real-time PCR and next-generation sequencing to study the prevalence of infectious diseases in the target study populations. Learning about sample testing under a
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condition leading to medical discharge following combat related trauma in our military. Learning opportunities include, but are not limited to: exposure to various aspects of pre-clinical research by
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annotation of these metabolomes using multistage fragmentation (MSⁿ) data, incorporating novel computational methods and strategies (e.g. spectral matching, network-based approaches, machine learning) where
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these powerful tools, and support learning in disciplinary or interdisciplinary contexts. In addition, the nature of the interaction between human and machine triggers new questions about the locus of agency and
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will a have a relevant PhD and medical degree alongside registration with the GMC at Specialist Registrar Garde or below. You will have a recent track record in histopathology and use of machine learning
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the appointment. The candidates should have a strong track record in at least one of the group’s research areas, preferably demonstrated by publications in high-impact venues. Experience with machine learning
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Requirements: A PhD degree in mathematics or related areas, with a strong background in topological data analysis (TDA) and machine learning on biomolecular data Proficiency in programming languages such as