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. Scientific Contribution Our group has strong publication record of 100+ first or senior author top-tier (ERA ranking A*/A) journals and technical conferences in the machine learning and medical AI field. His
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Adversarial Machine Learning (AML) is a technique to fool a machine learning model through malicious input. Due to its significance in many scenarios, including security, privacy, and health
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With success stories ranging from speech recognition to self-driving cars, machine learning (ML) has been one of the most impactful areas of computer science. ML’s versatility stems from the wealth
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The Center for Machine Learning Research (CMLR) is a newly founded interdisciplinary research center at Peking University. Its goal is to advance machine learning-related research across a wide
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based on matched-filter statistics. Detecting the unknown relies on the development of complex algorithms at the forefront of statistics, machine learning, and data science. This multi-disciplinary
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capillary pressure, and data-driven, physics-driven machine-learning. Applications are sought for a two-year postdoc position, and will work closely with an industry partner. The position will include a
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RAP opportunity at National Institute of Standards and Technology NIST Machine Learning Driven Autonomous Metrology System Location Physical Measurement Laboratory, Sensor Science Division
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RAP opportunity at National Institute of Standards and Technology NIST Machine Learning for Autonomous Genetic Engineering of Microbial Systems Location Material Measurement Laboratory
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RAP opportunity at National Institute of Standards and Technology NIST Machine Learning Methods for the Prediction and Correlation of Thermophysical Properties Location Material Measurement
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Project description: Nowadays, data-driven machine learning algorithms are well suited to solve real-world problems that require high-level prediction accuracy. However, it seems as if nothing beats