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: ? Experienced with modern data mining and machine learning methods. ? Proficient with computer programming in popular languages such as Python or Java. ? Experienced with large language models for text
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, Supervision of undergraduate and graduate BME students in modern machine shop operations, guiding and mentoring students, including guidance for students on design projects, prototype fabrication, and design of
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of the relationships between hypertension, its treatment, and ADRD risk among U.S. veterans, (2) statin use and ADRD risk and burden with quasi-experimental approach and machine learning methods, as well as (3) ongoing
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equivalent in education, training, and experience. - Excellent communication, organizational and database management skills; - Excellent quantitative and qualitative data analytic skills; - Computer fluency in
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an automobile or on bicycle. As such, the applicant may be required to pass a physical fitness job standards test. The Sergeant, working on a computer-aided dispatch platform, handles response to emergency
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; excellent oral and written communication, interpersonal skills, computer skills, and ability to conduct chart reviews. Must be able to learn and operate research project software. Equal Opportunity Employer
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to detail. S/he should have knowledge of climate-related issues and/or health. S/he should have a willingness to learn qualitative data analysis techniques. Proficiency or fluency in Spanish is highly
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. Seven years of related experience required. Ability to lift and move heavy items as needed. Manual dexterity, and mechanical aptitude. Capacity to safely use power tools when needed. Computer and tablet
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, drive belts, and sheaves without direct supervision. Shall be able to repair or fabricate parts using standard machine shop tools. Shall be able to troubleshoot, service, and perform preventive
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on the use of Machine Learning algorithms for rapid damage assessment. Research topics could focus on: the definition and use of novel damage sensitive features, physics informed machine learning, transfer