109 image-processing-and-machine-learning-"RMIT-University" Postdoctoral positions at University of Washington
Sort by
Refine Your Search
-
laboratory, which focuses on developing optical spectroscopy and imaging tools to solve global problems in reproductive health. The successful candidate will have the opportunity to work with a
-
analysis; Biomarker identification through the use of machine learning approaches; and Multi-omics data integration with genomics, transcriptomics and methylomics data. Job Description Primary Duties
-
pluripotent stem cell (iPSC) cultures is advantageous. Knowledge of flow cytometry, cell sorting, high-throughput screening and cell-based screening (e.g., luciferase assays, high-content imaging, massively
-
research group. The successful candidate will conduct original research in quantitative live-cell fluorescence microscopy, focusing on the actin cytoskeleton’s role in membrane trafficking processes in human
-
the University of Washington Privacy Notice for Demographic Data of Job Applicants and University Personnel to learn how your demographic data are protected, when the data may be used, and your rights. Disability
-
Personnel to learn how your demographic data are protected, when the data may be used, and your rights. Disability Services To request disability accommodation in the application process, contact
-
for Demographic Data of Job Applicants and University Personnel to learn how your demographic data are protected, when the data may be used, and your rights. Disability Services To request disability accommodation
-
. The postdoctoral associate will work in collaboration with supervisors and other scientists to study how global biospheres alter planetary processes in ways that are remotely detectable. This research will involve
-
. Experience with high-throughput molecular biology assays. Experience with complex functional experiments. Background in machine learning, AI, or data integration for genomic datasets. Familiarity with gene
-
processing of social information in patients with psychiatric conditions remain largely unclear. We use a suite of cutting-edge techniques, including in vivo multi-photon imaging, fiber photometry, and custom