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Field
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Postdoctoral Fellow with Professor Morgane Austern. Professor Austern’s group focuses on research in high-dimensional statistics, probability theory, machine learning theory, graph data, Stein method, ergodic
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spatial and temporal data analysis using advanced machine learning technologies. The successful candidate will become a part of an interdisciplinary team working to develop machine learning techniques
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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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to groom the next generation of leaders, thinkers, and innovators to thrive in the digital age. Located in the heart of Asia, NTU’s College of Computing and Data Science is an ‘exciting place to learn and
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, statistics, and machine learning. We offer a full-time position with the following benefits: Flexible working conditions including negotiable part time contract. Monthly gross salary: 54 - 72 thousand CZK
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Location_ONB: Kent Ridge Campus Posting Start Date: 31/10/2025 Job Description The successful candidate will work with Associate Professor Duane Loh on conducting research at the interface of Machine Learning
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digitalization and computation. To further develop machine learning tasks for scent signal classification/fusion. Set up and analyze experiments under different conditions. To propose a methodology/framework in a
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selection programs. Learning Objectives: By the end of this training/research experience, the fellow will be able to: Explain the structure and functional organization of the bovine genome and describe how
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JW, Surov SS, Liang Y, Parunov LA, Ovanesov MV. Effect of pH on thrombin activity measured by calibrated automated thrombinography. Res Pract Thromb Haemost. 2020 Jun 12;4(5):944-945. Learning
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dynamics, and machine learning methods in Grant-in-Aid for Transformative Research Areas (A): "Ion Congestion Science". Specific research backgrounds are not required but experiences of the following fields