126 machine-learning-"https:"-"https:"-"https:"-"https:"-"https:"-"https:"-"https:"-"U.S" positions at Yeshiva University
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The Learning Specialist will report to the Assistant Director of the Office of Academic Support and Counseling (OASC), and is responsible for assisting with conducting learning evaluations, and in
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documentation and diagrams as needed when assets are added or removed Other duties as assigned ADDITIONAL RESPONSIBILITIES Assist personnel of other departments as a computer resource Provide on-the-job training
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, internal consistency, and graduate outcomes that meet student learning, workplace, and placement expectations. Provides professional leadership and support, and serves as an educator, role model, mentor, and
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well as applications of multi-level modeling, machine learning, and/or AI for clinical prediction and estimation of novel dynamic phenotypes related to brain health and disease risk. The Program Director will report to
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internal consistency and alignment with programmatic accreditation standards. The position is integral in facilitating student learning within prescribed research courses, creating an educational environment
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Provide computer programming support of Beren Residence Life (including applications, check in, key and room assignments) Meet with graduate and undergraduate students about concerns, room changes
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support of Division scientific goals · Collaborate with staff implementing advanced data pipelines, including applications of machine learning and AI for clinical prediction and identification of novel
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software, including SPSS. Experience with survey software (e.g., Qualtrics) and the administration of psychodiagnostic and cognitive assessment measures and computer-based data collection would be
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machines, and telephones Knowledge of guidelines for recruitment, selection, and promotion is required Knowledge of the disciplinary and grievance procedures of the university is required Ability
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, national, and international organizations Developing research and grant opportunities . Experience & Education Background: Ph.D. in Computer Science, Computer Engineering or its related field from