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Oden Institute for Computational Engineering and Sciences | Austin, Texas | United States | 3 months ago
computational researchers to ensure high-quality molecular data generation. Train graduate students and laboratory personnel in molecular techniques and clean-room practices. Assist with laboratory management
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with BIG DATA (eg. NGS data in multi-TB scale). Experience using genome alignment software (bowtie2, bwa, tophat, etc.) is desired. Fluent in one programming language (Python, C, C++ or Java) and
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organizations with varying technical capacity. Explore applications of AI methods, including large language models and natural language processing, for extracting structured information from unstructured sources
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position in the Sinclair Lab at Harvard Medical School in Boston Massachusetts. The work of the Sinclair Lab is focused on analyzing large-scale biological datasets to identify key molecular pathways
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implementation of algorithms to analyze and integrate large data as well as the maintenance of datasets and shared tools. Lead and contribute to manuscript preparation, scholarly reports and presents at scientific
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. Applicants selected to become DSFs will be named to one of three fellowships based on their scientific background. The fellowships honor three prominent scientists who made a Big Science impact at ORNL. Dr
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in-house high-throughput and Big Data facilities for RNA-seq, scRNA-seq, microarray analysis, and bioinformatics including high-performance computation. You will participate in the research project
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mechanisms controlling muscle stem cell function. · Develop and evaluate pharmacological strategies targeting circadian pathways for muscle repair and disease treatment. · Analyze large-scale
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technologies into commercial products that solve big problems. We support research that universities, companies, and venture capital firms don’t fund because they view it as too risky. We prefer to use the word
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for this position will be twofold: 1) Discover disease mechanisms, biomarkers, and therapeutic targets in solid tumors through multi-omics data analysis of large pan-cancer datasets. The postdoctoral fellow will