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Applied statistics Network routing Agent-based simulation Behavioral economics Game theory Decision theory Machine learning Artificial intelligence Where will I be located? Both local and remote
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Learning about protein design and engineering Exploring cell-based and cell-free screening Applying high-throughput screening Utilizing bioinformatics, machine learning, and other computational approaches
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analysis of laboratory assay readouts, or processing and analyzing transcriptomics data (bulk or single-cell RNA-seq). Learning Objectives: Under the guidance of a mentor, the participant will have the
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the use of workflow tools, development environments, and resources to contribute to and implement shared bioinformatic workflows. Experiences may extend into training on Machine Learning and AI models as
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or viability of encapsulated bio-components. Why should I apply? This appointment offers training and travel opportunities to enhance your fellowship experience. Anticipated learning objectives include
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Doctoral Degree. Discipline(s): Chemistry and Materials Sciences (12 ) Computer, Information, and Data Sciences (17 ) Earth and Geosciences (21 ) Engineering (27 ) Environmental and Marine Sciences
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Master's Degree or Doctoral Degree. Discipline(s): Chemistry and Materials Sciences (12 ) Computer, Information, and Data Sciences (17 ) Earth and Geosciences (21 ) Engineering (27 ) Environmental
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Master's Degree or Doctoral Degree. Discipline(s): Chemistry and Materials Sciences (12 ) Computer, Information, and Data Sciences (17 ) Earth and Geosciences (21 ) Engineering (27 ) Environmental
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. This data was collected primarily in upland habitats, but a subset of the data focuses on changes in meadows over time. Learning Objectives: The selected fellow(s) in this project will have the opportunity
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also includes screening individual phytochemicals and extracts from additional plant materials to determine their anticancer and antioxidant activities. Learning Objectives: The participant will receive