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Field
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analysis of high-dimensional data (e.g., single-cell RNA-seq, phylogenetics, spatial data). Experience in R or Python. Application instructions: Please send a CV and a brief cover letter describing your
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experience with spatiotemporal analysis using R, Python, and/or comparable computer programming languages. Presenting results at national conferences. Leading the development of manuscripts with the aim
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-throughput screening approaches Experience with organoid culture systems Knowledge of bioinformatics tools and programming (R, Python) Track record of peer-reviewed publications Baylor College of Medicine is
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/EEG analysis) - Knowledge of R, Python, Matlab, shell scripts, or similar programming languages - Interest in mechanisms of psychopathology, particularly anxiety NOTE: Position tasks are generally
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in MATLAB/Python/R are desirable but not required. The position is part of a well-funded research program and will provide the opportunity to produce high-impact publications and establish
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, biostatistics, biomedical informatics or related fields OR a PhD degree in biology or related fields. Preferred Qualifications: A strong background in programming (e.g., Python or R or C++) is essential. Research
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analysis skills: Statistical analysis through SPSS, R, Design Expert, Origin, MATLAB, chemometric tools, or other software. Bioinformatics and grant writing. All positions are security-sensitive. Applicants
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University of New Hampshire – Main Campus | New Boston, New Hampshire | United States | about 1 month ago
stream chemistry data collected across a network of sites. The position will require downloading of data of field instruments and shared data repositories, and the development of code (R or Python based
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requires that after obtaining a PhD, eligible candidates for research associate appointments may not exceed a combined total of 5 years of relevant work experience as a post-doc and/or in an R&D position
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Engineering, or related. Strong experience in ODE/PDE modeling and simulation (MATLAB, Python, or R). Experience withnumerical methods, optimization, parameter estimation, and sensitivity and uncertainty