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Field
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, Effects, and Criticality Analysis (FMECA), functional FMECA, advanced sensing techniques, sensor and operational data fusion, data analytics, and machine learning algorithms for condition monitoring, fault
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, and formulation of clinical study design, image processing, machine learning, and statistical analyses to illuminate specific research questions. Among the machine learning techniques, deep learning
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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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manufacturing principles. Experience with machine learning methods and integration into hybrid modelling systems Demonstrated ability to clearly communicate research concepts and results in high-quality journal
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is to develop real-time truck-drone collaboration system to enhance Singapore safety and resilience and using learning-based approaches. Key responsibilities include: Collecting and analyzing relevant
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good collaborative skills within a team. You may also have strong theoretical and programming background in AI, machine learning, mathematical modelling including physics-based models, and/or robot
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Responsibilities: To perform pioneer research in scent digitalization and computation. To further develop machine learning tasks for scent signal classification/fusion. Set up and analyze experiments under different
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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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fluid dynamics. The successful candidate will be expected to work on all or a subset of the above topics, be proficient in working with large data-sets (observational or numerical), machine learning, and
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statistical machine learning techniques to mine self-reports and sensor data to gain new insights towards assessment and longitudinal monitoring of bipolar disorder; b) work on sleep datasets exploring