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of neural circuits controlling various aspects of natural behavior. See our lab web page (https://www.engertlab.org/research ) for more information about our publications and research interests. Basic
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addition to carrying out bench research using electrophysiological recording, the successful candidate will be expected to help develop data management software for managing and analyzing large volumes
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for genome sequencing data to enhance our understanding of disease processes including cancer and brain-related diseases. Areas of interest include: Identification of mosaic mutations in non-tumor cells and
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molecular and phenotype data. Including code that is production-ready for dissemination to other laboratories and for diagnostic use, and the management of large-scale data. They will join a team of
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, machine learning and AI, statistical computing, big data and AI applications and prediction in biology, medicine and infectious diseases. Potential research projects include (but are not limited
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-disciplinary team of researchers, including bioinformaticians, pathologists, oncologists, and computer scientists, and conduct original research on computational pathology. Digital pathology images contain rich
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submit with their application contact information for two to three references from experts at the ladder faculty ranks or highly accomplished senior researchers from corporations or research institutes
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Data Analysis Center that manages multi-omic data (e.g., Illumina/PacBio/ONT Whole Genome Sequencing (WGS), RNA-Seq). The ideal candidate will have a deep understanding of next-generation sequencing (NGS
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Details Posted: Unknown Location: Salary: Summary: Summary here. Details Posted: 06-Mar-26 Location: Cambridge, Massachusetts Categories: Academic/Faculty Computer/Information Sciences Internal
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to compare the genetic architecture of rare vs. common genetic variation 2. Developing methods to analyze GWAS data using graphical models and genome-wide genealogies 3. Developing methods to integrate rare