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academic and professional goals. You will also engage in activities and research in several areas. Unique learning opportunities of this Graduate Fellowship may include, but are not limited to: New proteomic
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results, and collaborations. The Fellow will also have opportunity to engage with project collaborators to develop and enhance their network of subject matter experts. Outreach may include travel. Learning
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stakeholders, and collaborate with other scientists, other ORISE fellows, Hub leadership, and partners to determine potential solutions and pathways for optimizing productivity. Learning Objectives: The Fellow
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resilience and energy-savings. Learning Objectives: The Fellow will build skills in: Building relationships with stakeholders Tool generation for producers and technical exerts Creating educational materials
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stakeholders, and collaborate with other scientists, other ORISE fellows, Hub leadership, and partners to determine potential solutions and pathways for optimizing productivity. Learning Objectives: The Fellow
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assimilation and/or machine learning in combination with other remote sensing and in-situ data, and the insights into geophysical fluid dynamics. There are rewarding opportunities to make a big impact through
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publications, preferably on the climate-public health nexus. Experience with Artificial Intelligence (AI) and Machine Learning (ML) techniques. Point of Contact Mikeala Eligibility Requirements Citizenship: LPR
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linked to environments, chemical pathways, and feedback mechanisms. The tools of artificial intelligence (AI) and machine learning (ML) may be uniquely suited to addressing elements of this challenge
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to, Learning techniques involving small and large animal handling, organ dissection, plethysmography, and microscopy. Physiological and clinicals assessment using medical techniques and devices. Sample analysis
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to support secure and reliable communication systems essential for military and research applications. What will I be doing? Under the guidance of a mentor, you will engage in research focused on network