33 condition-monitoring-machine-learning Postdoctoral research jobs at University of Oregon
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to work collaboratively with a team and community partners • Ability to work independently on highly technical projects • Strong computer, statistical, and technical skills Preferred Qualifications
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-capacitive devices and magnetoelastic sensors, that can be integrated into implants to monitor mechanical forces, strain, and physiological changes in real time. These “smart implants” are designed not only
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state agencies, and other universities. Consisting of 10-15 employees including faculty, undergraduate, and graduate students, the Lab prides itself on providing experiential learning opportunities
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• Experience performing experimental and theoretical characterization of acoustic fields and cavitation monitoring • Proficiency in programming, particularly Matlab or Python • Experience using the Verasonics
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machine learning are desirable, applicants from other quantitative fields (e.g. math, physics, statistics, computer science) who are eager to learn about neuroscience are highly encouraged to apply as well
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. Postdoctoral Research Scholars will conduct research under the direction of a faculty member to acquire research training. In addition, to further career development, the postdoctoral research scholar and PI
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, immersive technology, philosophy, and anthropology. Overall, our research is guided by the belief in the importance of conducting research in a supportive community of learning. The successful candidate will
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• Effective communication skills Preferred Qualifications • Expertise in one of the following areas: Environmental or Performance Physiology, Machine Learning, Motion Analysis, Multiscale Modeling
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opportunity to acquire research experience, contribute to program goals, and receive an annual performance evaluation. Postdoctoral Research Scholars will conduct research under the direction of a faculty
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Apply now Job no:535376 Work type:Faculty - Pro Tempore Location:Eugene, OR Categories:Instruction, Computer and Information Science, Data Science Department: CAS CIS Computer & Information