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spectrometry, protein-protein interactions, recombinant expression/purification. Preferred Qualifications Equipment Utilized Must be familiar with Microsoft Office, Adobe Photoshop and Illustrator, and R. Must
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must have the following essential skills: Strong background in plant breeding and genetics Strong computer skills and proficiency in R or other programming languages Outstanding interpersonal and
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completed Ph.D. within the last 5 years in Computational Biology, Bioinformatics, Machine Learning, Artificial Intelligence, Virology, or a related field Strong programming skills in Python, R, or Julia, with
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The Postdoctoral Appointee will be part of a R&D group conducting use-inspired research supporting the development of next-generation energy technologies such as nuclear fuel recycling and
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, Matlab, R, etc.) is also advantageous. Department Contact for Questions Questions regarding the position or application process can be directed to: Prof. Van Stappen, Department of Chemistry, Indiana
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. Experience with programming languages such as Python, R, or MATLAB and experience with relevant tools and frameworks for data analysis and machine learning. Experience with database technologies, particularly
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 7 hours ago
- Proficiency in programming (e.g., Python, R, or similar). - Experience with large-scale omics data analysis. - Excellent communication skills. Preferred Qualifications, Competencies, and Experience - Solid
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or machine learning. Strong programming skills in Python/R. Solid foundational knowledge in human genetics and genomics. Experience working with next-generation sequencing data. Baylor College of Medicine is
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values. Application Materials Required: Further Info: https://medicine.duke.edu/divisions/gastroenterology/education-and-training/gi-r Division of Gastroenterology DUMC Box 3913 Durham NC 27710
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, genotype data, biomarkers, etc.) is required. Desire to apply your skills in data analysis to utilize bioinformatics methods (e.g., from R/Bioconductor) or machine learning tools (e.g., using Python packages