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influenced today’s widely used AI products. For more details, please view: https://www.ntu.edu.sg/eee We are looking for a Postdoctoral Fellow to lead research on AI training algorithms. The role will focus
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of steel compositions. The future potential of the model / numerical tool to replace costly trial- error method will also be evaluated. The Institute Jean Lamour (IJL) is a joint research unit of CNRS and
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Science and Artificial Intelligence. The lab models, simulates, and analyzes social phenomena using computational, experimental, and theoretical methods. We pursue consequential questions
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and spoken English. Knowledge of Czech is not required. Experience in one or more of the following areas would be an advantage: gravitational-wave modelling; numerical relativity; cosmological data
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one programing language (e.g., R, STATA). · Excellent quantitative analytical skills, particularly in longitudinal modeling, administrative data analyses, and causal inference methods. Understanding
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additive manufacturing. The role will focus on thermal field modelling, multi-physics numerical simulations, machine learning and process parameter optimization. We expect the candidate to use data-efficient
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on model papers using a dedicated micro-tensile machine coupled with 3D real-time in situ observation using synchrotron X-ray microtomography (ESRF). • 3D Image analysis routines will be used to identify
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addition to numerical simulations using models based on fluid-dynamics, research employing mathematical, statistical or machine learning method, as well as experimental research using the facilities at the Ujigawa Open
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to design data models that support downstream reporting and self-service analytics. Experience with healthcare data standards and source systems (e.g., OMOP, Epic Clarity/Caboodle), including cohort discovery
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, observations, a hierarchy of numerical models, and machine-learning methods to understand their formation, dynamics, and predictability. The successful candidate will have substantial freedom to develop