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and MySQL databases in HPC environments for large-scale data analysis. Collaborate with interdisciplinary teams to support data-driven biological discovery. Publish scientific papers, release datasets
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(EHR) data, large data sets, or geospatial analysis. A record of submitting external funding applications (e.g., F31, T32, foundation grants). Background Investigation Statement: Prior to hiring
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to improve the early detection of pancreatic tumors and improve patient management. Different machine-learning approaches will be compared, and models validated on data prospectively collected. The position
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analyses, latent modelling, multilevel modelling). Data Cleaning and Management. Engages both independently and under supervision in data management and data cleaning and organization in large (N~100,000
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and their natural enemies. This research will leverage advanced 'omics' technologies and 'big data' analytics to unravel complex pest-natural enemy interactions, understand host associations, and
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produce new plant narratives for the Plant Humanities Lab , using the rare book collection at Dumbarton Oaks and other special collections, as well as large digital repositories such as iDigBio and the
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. The Fellow will work in close partnership with the lab's experimental team to build and apply analytical frameworks that translate these data into mechanistic insight and therapeutic hypotheses. As part of
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internal institution systems may be submitted. Click here for detailed information about acceptable transcripts. A current resume/CV, including academic history, employment history, relevant experiences
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climate. Observational work would include data from GRACE, SMAP, GPM or in-situ stations. Model diagnosis and analysis can include CLM, VIC, CLSM, and LIS frameworks including GLDAS and NLDAS. Model
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Details Title Postdoctoral Fellow, Digital, Data, and Design Institute - Digital Reskilling Lab School Harvard Business School Department/Area Position Description The Digital Reskilling Lab, led by