392 machine-learning-"https:"-"https:"-"https:" Fellowship positions in United States
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. Cross-Disciplinary Fellowships (CDF) are for applicants with a Ph.D. from outside the life sciences (e.g. in physics, chemistry, mathematics, engineering or computer sciences), who have not worked in
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conditions. Anticipated outcomes of the project include criteria for selection of fungal genotypes that will be developed into new biocontrol products for mitigation of crop aflatoxin contamination. Learning
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of the opportunity involve various outdoor conditions requiring moderate exertion and traversing the landscape of the MEF. Additionally, the fellow will experientially learn about and participate in the Forest Service
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culture. Must be experienced working with laboratory mice. Must be willing and able to learn to assist with medication administration, surgical procedures, post-operative monitoring, and sample collection
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Postdoctoral Fellow - Materials Chemistry, Texas Materials Institute, Cockrell School of Engineering
or parallel reactors Collaborate with computational scientists to integrate machine-learning models for closed-loop materials discovery Collaborate with companion postdocs on functional materials
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both the development and regulation of oligonucleotide drugs. Learning Objectives: Under the guidance of the mentor, you will receive instructions on utilizing chromatography, mass spectrometry, and
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Center for Biologics Evaluation and Research (CBER) | Silver Spring, Maryland | United States | about 16 hours ago
of research results, and preparation of scientific manuscripts. Learning Objectives: Through this training, you will learn the challenges for benefit-risk assessment of biological products, FDA framework, and
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, diversity and educational excellence. Learn more about the Ferris Mission and community at ferris.edu . The University actively seeks applications from women, minorities, individuals with disabilities
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capabilities (through API calls) into the InfoViP platform while developing an enhanced user interface that incorporates various functionalities to support adverse event analysis. Learning Objectives: You will
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may include—but are not limited to—AI-based grid operation and planning, reinforcement learning for distributed system coordination, electricity market design, pricing mechanisms for reliability and