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data and high-throughput, multi-dimensional -omic data to study neurodegeneration and diseases of the central nervous system, with an emphasis on Alzheimer disease, Parkinson’s disease, and other
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include experience with fiber sensing, machine learning tools, and big data workflows. Instructions To apply, candidates will submit materials via Interfolio, comprising (1) a letter of interest describing
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be involved in projects to perform big-data research, bundling genetics, multi-omics, biomarker, clinical, and histopathological data, to harness the full range of biologically relevant data to better
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genomic tools and protocols for large scale genetic mark recapture (GMR) programs in Atlantic Bluefin Tuna (Thunnus thynnus) in the northwestern Atlantic. The project is a collaboration among Lorenz Hauser
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both dry and wet lab operations. Dry Lab Operations: Analyze large-scale datasets including single-cell and bulk RNA sequencing, microbiome data, proteomics, and other high-throughput platforms. Apply
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on “big data” studies in health and diseases, including Alzheimer’s disease and others such as schizophrenia, psychosis, autism, etc. We collaborate with major research universities worldwide as
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: Experience with rodent behavior and olfaction. Proficiency in Python or other programming language for large data analysis. Experience with quantitative approaches to studying animal behavior. Experience with
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aiming to investigate parent infant interaction with a focus on music and speech at the University of Washington Seattle Campus. This job focuses on analyzing a large longitudinal dataset (video-audio
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research participants. With this research, we have a unique opportunity to address the large unmet need of treatment-resistant disorders of brain function. We have applied the technology to patients with
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and staff, and providing support in applying for additional research grants. There is also opportunity to conduct analyses of already-collected data. This position has availability for onsite or remote