750 machine-learning "https:" "https:" "https:" "https:" "https:" "https:" "https:" "Simons Foundation" positions at Cornell University in United States
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diverse cuisine. Cornell Dining is looking for customer-focused, high-energy, inspired, and ready-to-learn individuals who have a passion for food! Applications will be reviewed on a rolling basis. Wage per
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, and the ability to read related scientific papers on cancer combination therapy. It would also require expertise in relevant AI methodology, such as deep learning architectures for property prediction
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our benefits: https://hr.cornell.edu/benefits-pay . Follow this link to learn more about the Total Rewards of Working at Cornell: https://hr.cornell.edu/jobs/your-total-rewards . Our leave provisions
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community. Is motivated to learn and takes initiative to be proactive Ability to work independently without immediate supervision Demonstrated experience utilizing independent judgment and problem solving
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, systems or molecular biology or related fields. A track record of independence, and a high level of enthusiasm for interdisciplinary research, learning new skills and a demonstrated ability to well as part
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Machine Operator S02, Cornell Dining - Multiple Positions Available Student and Campus Life (SCL) inspires transformation in all Cornell students on their journey of individual, academic and personal
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—are encouraged to apply, with opportunities to grow in other areas through collaborative mentorship and team-based learning. Department of Human Centered Design The Department of Human Centered Design (HCD https
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working on their own research and connecting to colleagues across the university. Depending on interests and feasibility, they may be able to teach and/or engage in off-campus fieldwork with Professor
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• Instruct veterinary students throughout the curriculum and extra-curricularly on management of hoof disorders of the horse o Didactic lectures and interactive sessions o Provide 2-week elective farrier
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materials by bringing together computer scientists, materials researchers, and data scientists to tackle knowledge- and data-centric challenges at the intersection of AI and materials science. In this AI-MI