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), physics-informed generative modeling and representation learning, domain adaptation, ML-assisted lattice field theory, and quantum algorithms and Hamiltonian simulation for high-energy physics, etc
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emission of a hydrogen plasma. Extend the quantum computing algorithm to a time-dependent system. Formulate the quantum scattering problem of electron impact ionization and excitation in a hydrogen and
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the position description. Preferences The ideal candidate will have experience with wearable sensors and/or remote monitoring approaches and strong programming (e.g., R, Python, or similar) and writing skills
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anticipated include imaging phantom-based evaluation of quantitative SPECT/CT; reconstruction algorithm development; establishing a secondary standards laboratory for unsealed source metrology through gamma
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the Institute of Sensor and Actuator Systems, in the Research Unit of Microsystems Technology, TU Wien is offering a position as project assistant (PhD position). The PhD position is planned for a total duration
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and training. -Support processing and integration of datasets, including UAV imagery, satellite data, IoT sensor data, and field observations. -Contribute to workflows for AI/ML applications, crop
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, research databank that integrates data from UF student-athletes on health, nutrition, academic performance, and sports performance, including wearable sensors at practices and games. The successful candidate
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join a growing, interdisciplinary team whose projects span laboratory-level and nationally significant DOE missions. Essential Duties and Responsibilities Develop novel machine learning algorithms and
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preprocessing IoMT network traffic datasets. Implement and evaluate machine learning algorithms (e.g., logistic regression, SVM, random forest) for intrusion detection. Develop prototype software tools (e.g
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and implementing innovative solutions at the intersection of sensor data collection, machine learning, and real-time decision-making. Specifically, the candidate will contribute to projects focused