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, United States of America [map ] Appl Deadline: (posted 2025/06/24, listed until 2026/06/23) Position Description: Apply Position Description Overview Susquehanna is expanding the Machine Learning group and seeking
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Physics Operations Research Appl Deadline: (posted 2025/06/24, listed until 2026/06/23) Position Description: Apply Position Description Overview Susquehanna is expanding the Machine Learning group and
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Title: PhD Student Mentor-Learning Technologies Employee Classification: PhD Student Mentor Campus: University of North Texas Division: UNT-Provost SubDivision-Department: UNT-College of Information
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to learn the following skills: 1. Ultrasound imaging 2. Transcranial doppler 3. Recording and analyzing physiological data including intracranial pressure using power lab, Moberg, ICM+, or similar software
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to learn the following skills: 1. Ultrasound imaging 2. Transcranial doppler 3. Recording and analyzing physiological data including intracranial pressure using power lab, Moberg, ICM+, or similar software
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, Resnick Campus in the Bronx, the Gruss Institute in Jerusalem, the Boys High School in Manhattan and the Girls High School in Queens. From the distinguished faculty who teach here, to the dedicated staff
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) Developing machine-learning based exoskeleton controllers to work across tasks 2) Designing and validating new robotic lower-limb prostheses 3) Exploring other high-risk high-reward research areas related
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University of Massachusetts Medical School | Worcester, Massachusetts | United States | about 6 hours ago
and cell culture techniques are desired. The candidate is expected to work closely with an interdisciplinary research team and must be motivated to acquire new experimental skills. PROJECT DESCRIPTION
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to design and implement machine learning techniques and algorithms. * Demonstrated expertise in the Linux computing environment. * Excellent planning, organization and execution skills. * Positive attitude
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informatics, biomedical engineering, statistics, or related fields. The lab is engaged in developing novel deep learning and AI-based technologies for digital biopsies from medical images and real-world