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analysis and machine learning methods applied to protein structure determination using single-particle cryo-electron tomography (ET). The candidate will contribute to the design, development, and
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. The project goals are to evaluate the geochemical characteristics of acid mine drainage (AMD) fluids and treatment solids at sites that are known to be enriched in rare earth elements, cobalt, and other metals
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application to medical imaging (e.g., MRI) · Experience with MRI data analysis, network science, graph theory, topological analysis, or related computational approaches, especially in Alzheimer’s
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analysis using appropriate machine learning techniques and contribute to the writing of technical papers and research proposals. Duke is an Equal Opportunity Employer committed to providing employment
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with Dr. Kate Hoffman to define and lead specific research objectives aligned with the funded aims. Responsibilities will include project management, coordination of data collection and analysis
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including but not limited to microbial ecology, biochemistry, genomics, biostatistics, molecular biology, microbiology, evolutionary biology. Familiarity with metagenomics data analysis, microbial
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/bioinformatics, and data science. Work Performed · Work in highly collaborative inter-disciplinary environment with clinicians, econometricians, statisticians, and data scientists · Lead statistical analysis
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decisions focusing mainly on interpretable machine learning and its applications. The candidate must be an expert in music generation and Schenkerian analysis. The candidate will be responsible for working
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Bioinformatics expertise required for scRNAseq analysis. · Previous cell culture experience. · Perform molecular, cellular, biochemical and immunological analyses. · Optimize and troubleshoot experimental
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, engaging with other data analysts, students, post- docs and faculty on the team Conduct comprehensive high-throughput multi-omics data analysis and epidemiological analyses; Apply biostatistics and cancer