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Field
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. The goal of this research is to enhance power quality and security for Naval power systems using non-intrusive approaches, advanced signal processing tools and machine learning to advance anomaly detection
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the interview process. Certain visa types may limit work location. Individuals must meet work location sponsorship requirements prior to employment. Benefits We invite you to visit Harvard's Total Rewards website
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may include some or all of the following: interview data; self-report data; observational data in the home; health specimen collections. Review data for document accuracy and processing as needed
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effective oral and written communication skills. Must be computer literate with proficiency and working knowledge of database and reporting tools such as Microsoft Word, Excel, and PowerPoint. Must have the
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screening, treatments, and visits. Data entry, management and calculations using a computerized database, word processing and spreadsheet software; review data input for accuracy and completeness. Actively
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by supporting charitable, scientific, cultural, educational, and literary projects. The online application process is now CLOSED for academic year 2025-2026. ***** Important Information When
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activity submit a summary of the research activity at the end of each semester. Discipline Specific Required Qualifications Health care related background Knowledge of searching databases Computer knowledge
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Science / Electrical and Computer Engineering Division Provost - Academic Affairs FTE .5 Scope of Job Maximum appointment is limited to twenty (20) hours per week (50% FTE) during the Fall and Spring semesters. Maximum
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Analysis and apply today! This work will advance novel research focused on sensor-based in-situ process monitoring, data correlation to end part quality, data driven machine parameterization, and data
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regarding your status within the process. In this account, you are able to track your applicant status in "My Applications". To be considered eligible for the position as an internal candidate, departmental