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imaging, tissue dissections, harvesting, cryosectioning, and histology/imaging is highly desired. Prior experience with single cell analysis, spatial transcriptomics analysis, python, R is highly preferable
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model APIs, cloud computing environments, and R for additional statistical analysis. For decision support prototype development and evaluation, web-based user interface design, human-computer interaction
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the use of R and/or Python Basic understanding of statistical modeling, and machine learning Understanding of high-throughput sequencing techniques including whole genome, whole exome, targeted capture, RNA
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knowledge in bioinformatics, machine learning, statistics and programming skills (R, Python, or MATLAB) are required. The ideal candidate should demonstrate a record of publications in the area. Knowledge in
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, mathematics, physics, or a related field. The ideal candidate should demonstrate a record of publications in the area. Strong knowledge in machine learning, statistics and programming skills (R, Python
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culture, ELISA, protein purification, DNA/RNA isolation, and PCR. Experience in flow cytometry is preferred. Experience with CyTOF, single cell RNA-seq, and bioinformatics tools like for example R is
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confocal microscopy. Computational experience with R and bash processing. Computer experience with spreadsheet and word processing applications. Experience or willingness to learn quantitative analysis
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latent variable models (especially factor analysis, item response theory, and growth modeling) and coding in R. Strong collaborative skills and ability to work well in a complex, multidisciplinary
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Expertise and hands-on experience using LLMs, Machine Learning, Deep Learning frameworks, Natural Language Processing, etc. Proficient programming skills in Python and R and working knowledge in SQL Strong
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.) and proficiency in data analysis software (such as R, Mplus, SPSS). Extensive experience interpreting research data and summarizing findings via written reports and oral presentations. Strong record