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prediction, gene-environment interaction, cross-population analysis, and integration of genomic data with longitudinal electronic health records. The scholar will have opportunities to lead projects using
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, analyzes, interprets and communicates data (written and oral), including bioinformatic and statistical analysis of soil and plant health and microbiome datasets. 40% - Designs and conducts field
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laboratory personnel and general lab maintenance, and interactions with project collaborators. Essential Duties: 50% - Data collection, organization, analysis, interpretation and communication
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colleges and divisions. The Postdoctoral Scholar will contribute to all phases of the research lifecycle, from concept development and proposal preparation to data collection, analysis, publication, and
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assistants. The incumbent will coordinate the management, retention, cleaning, and analysis of research data, administration of both caregiver and child measures and assessments, and conduct data management
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volumetric and surface data at a scale that manual analysis cannot match: tomographic volumes, surface meshes, point clouds, and derived geometric measurements across hundreds or thousands of specimens. The
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scientific mentor in the Department of Biomedical Informatics; designs and develops novel computational tools for biomedical data analysis; performs large-scale analysis using omics data; assists in
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electronic properties. Develop and apply advanced data analysis workflows for large microscopy datasets. Required Education: Ph.D. in Materials Science, Physics, Applied Physics or equivalent Desired
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research experience in agricultural data analytics, remote sensing, machine learning, spatial data analysis, sensor systems, or related areas. Relevant experience obtained during Ph.D. research may be
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research skills, data analysis proficiency, and statistical expertise, coupled with exceptional written and verbal communication skills. Requires previous work in chronobiology, including a