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economic assessments machine learning or proxy-model based methods field scale simulation geological features geomechanics reactive flow The PhD fellow are not expected to master all these topics. Project
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Engineering, or related field. Research experience with Artificial Intelligence/Machine Learning/Large Language Model. Publication track record in a series of top tier conference papers e..g, in NeuRIPS, ICLR
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PROGRAMME AND TRAINING: - extend the knowledge of the state of the art in machine learning for lung cancer imaging data; - identify and select the appropriate methods for the study in question; - develop
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models to characterize lung cancer based on a non-invasive methodology. 3. BRIEF PRESENTATION OF THE WORK PROGRAMME AND TRAINING: - extend the knowledge of the state of the art in machine learning
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worked in MRI research previously or have strong computational / AI / machine learning skills used in other areas of research. Essential criteria PhD qualified in relevant subject area Ability to work as
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similar structures from the same population. New machine learning, sensing and digital twin technologies will be developed with the aim of driving new standards for safer, greener structures in the future
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, friendly and inspiring, and the position represents a unique opportunity for career development for a hard-working candidate. Main responsibilities Develop and apply machine learning and statistical modeling
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with carrying out original research to develop new machine learning approaches to link different scale geochemical-mineralogical-petrophysical datasets within a 4D geological framework. An initial focus
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. The research will help to suggest best practices for machine learning integration in de-risking CO2 storage sites. We seek a candidate with a strong background in one or more of the fields of rock physics
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and students, it offers a friendly and international work environment Learn more about CQT at https://www.cqt.sg/ Job Description We are looking for a Research Fellow (RF) to join the team and explore