37 finite-element-analysis Postdoctoral positions at Cornell University in postdoctoral
-
strong background in both materials physics and computation to join our Quantum Materials team. We seek candidates who are interested in developing cutting-edge tools for analysis of comprehensive single
-
Quantitative genetic analysis of AMP allelic variation in natural populations Molecular evolutionary and population genetic analysis of AMPs in D. melanogaster and across the genus Drosophila Anticipated
-
of Integrative Data Analysis.” As a postdoctoral associate, you will focus primarily on data analysis and manuscript preparation, with opportunities to publish as first author as well as collaborate on papers with
-
secondary data sources for research; use and analysis of quantitative data in concert with extensive in-depth literature reviews and related written summaries targeting AI topics; completion of human subjects
-
for advanced data analysis and/or experimental control (e.g., Python, SPEC, MATLAB, etc.) Experience with relevant sample preparation and lab-based analyses (e.g., SEM, Raman) Experience with or interest in
-
(ATAC-seq, single-cell and single-nucleus RNA-seq, splicing variant analysis) with the sex-determination cascade to dissect how chromatin accessibility, transcriptional regulation, and alternative
-
with a dissertation that includes a focus on host-microbe interactions, microbial community analysis, or microbial metabolism. Demonstrated expertise in one or more of the following: microbiome
-
community analysis, or microbial metabolism. Demonstrated expertise in one or more of the following: microbiome sequencing data analysis (shotgun metagenomic, and/or metatranscriptomic), microbial
-
. Anticipated Division of Time Data collection, analysis, and interpretation (70%) The postdoctoral associate will design, execute, and interpret all experiments related to the project in collaboration with other
-
of the experiment, from data analysis to detector operations and HL-LHC detector upgrades. The successful candidate is expected to engage actively in analysis of CMS data and will have considerable freedom in