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Field
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PERA retirement account. Position Summary The Research Assistant (RA- Temporary Hourly Administrative) Program facilitates opportunities for recent graduates to participate in faculty/administrator
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education technology. The RA will have the flexibility to work on-site or remotely as needed and will gain valuable experience on an interdisciplinary project that bridges computer science and learning
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journals in the field of large vision models, computer vision, and so on. Additionally, the appointees will be responsible for submitting grant proposals to various funding bodies. Furthermore
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, knowledge, and skills related to equity, diversity, and inclusion PREFERRED QUALIFICATIONS Computer Skills Required: MS Office, data analysis software. Ability to work effectively independently and in a team
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Internal Training Medical insurance – including 100% paid employee medical coverage for full-time employees Dental Insurance Vision Insurance Long and short-term disability Retirement Plan Options Paid time
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splitting and C–N coupling reactions. Work includes computational modeling of carbon-based materials, conducting simulations to understand reaction mechanisms, and developing and applying machine learning
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personal and professional well-being. What we offer: Medical , Dental , and Vision Flexible Spending Account Retirement Programs Disability Plans Life Insurance Accident Plan Paid Time Off and Other Leave
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that are leading the way in emerging technologies through programs such as computer engineering, information technology, and ocean engineering. We’re developing the next generation of business leaders, while also
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Harvard University Faculty of Arts and Sciences | Cambridge, Massachusetts | United States | 3 months ago
Rewards website (https://hr.harvard.edu/benefits-wellbeing ) to learn more about our outstanding benefits package, which may include: Paid Time Off: 3-4 weeks of accrued vacation time per year (3 weeks
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, including: (i) estimating heterogeneous effects using RDD and causal machine learning methods; (ii) modeling dynamic longitudinal health data; and (iii) developing and refining statistical models and tools