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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 2 months ago
inform observable macroscopic properties as part of the activities of the UNC Superfund Research Program (SRP) (https://sph.unc.edu/superfund-pages/srp/). This work involves running, developing, and
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Immunology Posting Number R260043 Posting Link https://www.ubjobs.buffalo.edu/postings/61543 Employer Research Foundation Position Type RF Professional Job Type Full-Time Appointment Term Salary Grade E.89
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existing and new computational methods to study multiscale processes in catalysis and photochemistry. Other projects that align with our general interest are also possible. Please see https://sdonglab.org
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selectivity, spin-polarized electron transport. • Skilled in the use of SEM, TEM and spectroscopy for nanomaterial, and thin film characterization. • Proficiency in Python, MATLAB, OriginPro, R or a similar
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Qualifications: Experience analyzing oral microbiome datasets (16S, shotgun metagenomics, or metatranscriptomics). Advanced programming and data science skills in R, Python, or other relevant languages
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Description Primary Duties & Responsibilities: Information on being a postdoc at WashU in St. Louis can be found at https://postdoc.wustl.edu/prospective-postdocs-2/ . Working Conditions: This position works in
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experience with deep learning (DL) methods. Demonstrated proficiency in Python and machine learning frameworks (e.g., PyTorch, Jax, scikit-learn) applied to genomic/related datasets. Experience with sequence
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community visit: https://greateriowacity.com/build/area-advantages/ The position will begin in Fall 2026, with flexibility in start date based on candidate availability. The initial appointment is for 1 year
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R, Python, or similar tools. Familiarity with plant growth chamber experiments, controlled inoculation systems, or compartmented experimental designs. Experience integrating multi-omics datasets
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 6 days ago
reusable libraries in Python, Scala, and/or C++, taking advantage of Spark, Hadoop, and other tool stacks as appropriate. * Developing computational and algorithmic approaches to understanding