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Field
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and personalized learning experiences Position Summary : This role is ideal for a highly motivated individual who thrives in dynamic environments and excels at translating vision into action. Working
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. As a Carnegie Doctoral/R2 institution, our world-class scholars instruct about 26,000 students in associate's, bachelor's, master's and doctoral level degree programs. Whether you are seeking the charm
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Associate will contribute to ongoing projects and have the opportunity to develop independent research aligned with the aims of the ADN lab. Current work focuses on machine learning and multivariate decoding
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AgriLife is uniquely positioned to improve lives, environments and the Texas economy through education, research, extension and service. Click here to learn more about how you can be a part of AgriLife and
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a position combining project management, machine-learning model development, data management/analysis, and manuscript writing for publication. Preference will be given to applicants with (1
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. Demonstrated expertise in interdisciplinary research with technical and clinical teams and patients desired. Experience leveraging machine learning for human musculoskeletal biomechanics applications desired
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. Qualifications PhD Certificates/Credentials/Licenses n/a Computer Skills MS Office and willingness to learn software used in the research lab Supervisory Responsibilities No Required operation of university owned
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. Qualifications PhD Certificates/Credentials/Licenses n/a Computer Skills MS Office and willingness to learn software used in the research lab Supervisory Responsibilities No Required operation of university owned
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from varied sources, and machine learning methodologies Required Application Materials: 1. A cover letter describing: a. Your interest in this position b. Your relevant training and experience c. Your
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-Sigler Institute for Integrative Genomics and the Computer Science Department at Princeton University. We seek candidates with computational biology, bioinformatics, computer science, machine learning