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collaborative team performs high-impact studies that allow them to develop new strategies to ameliorate dysbiosis and neuroinflammation and reduce chronic disease burden. Key Responsibilities: Bioinformatics
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: Bachelor’s degree in bioinformatics, Biostatistics, Computational Biology, Data Science, Computer Science or related field A combination of education and related technical/paraprofessional experience may be
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Bioinformatician at the intermediate or senior level. The Breuss laboratory is focused on employing and developing statistical machine learning, bioinformatic algorithms, and related approaches for the detection
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Cancer Center, as well as Genomics, Bioinformatics, and Organoid Shared Resources. Why work for the University? We have AMAZING benefits and offer exceptional amounts of holiday, vacation and sick leave
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analyses such as RNA‑seq library prep, single‑cell workflows, qPCR, Western blotting, ELISAs, and multiplex assays. Integrate multi-omics datasets using R or Python; collaborate with bioinformatics core
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immunology and/or immunotherapy research Prior experience with in vivo mouse experiments Proficiency with flow cytometry Prior experience with CRISPR screens and RNA-Seq Proficiency in bioinformatics and
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early development of the placenta, and a basic understanding or willingness to learn bioinformatics is desired. The candidate should be proficient in, or highly motivated to learn complex 3D culture
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to disseminate the study results. Collaborate with and support Principal Investigators (PI) and other stakeholders in the area of bioinformatics and data analysis. Assist with the design and development of major
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activities, participate in project meetings relevant to the design, development, implementation, and maintenance of data management system Perform scientifically rigorous data management and bioinformatic
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learn new research skills based on your interests. These may include performing and analyzing high-throughput drug screening experiments, bioinformatic analyses (single-cell, metabolomics and proteomics