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Field
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successful in this role, we are looking for candidates to have the following skills & experience: Essential criteria PhD qualified in relevant subject area* Experience developing deep learning segmentation
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research into planet formation/protoplanetary discs or the ISM/star formation and may also have some experience in statistical methods and/or machine learning. Dr Winter and QMUL are committed to improving
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Transport Systems Laboratory, equipped with cutting-edge technology that supports research in autonomous transport, decarbonisation, machine learning, travel behaviour, air transport management, and transport
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integrating Machine Learning (ML) with physics-based degradation modelling will enhance early fault detection, reducing unplanned downtime. This PhD is hosted at Cranfield University, a global leader in
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Desirable criteria Experience of advanced statistical and/or machine learning methods, such as longitudinal analysis methods, latent variables models, clustering algorithms, missing data and clinical trial
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an exciting opportunity to a graduate with the relevant skills and knowledge to develop and implement machine learning techniques to derive new-to-sector advanced insights from Aids to Navigation maintenance
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Introduction to Programming with Python Supervised Machine Learning Expected Qualifications: Minimum of a Master’s degree related to the area of teaching, with a preference for an earned doctorate (PhD or DBA
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needs. While muscle imaging from well-characterised patients and transcriptomic technologies provide rich data, these remain under-utilised for predictive modelling. Using machine learning, this project
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web technologies Experience in teaching bioinformatics Previous experience with AI and/or machine learning approaches Interest in reproductive health and/or development of clinical tools and algorithms
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The Vietnamese-German University (VGU) is seeking a highly qualified full-time lecturer in IC Design and Computer Architecture. Candidates must hold a PhD in this field or a closely related field