97 software-testing "Computer Vision Center" Postdoctoral research jobs at Rutgers University
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Experience developing software with Python, R, and/or Julia Experience with machine learning and AI algorithms and tooling (e.g. PyTorch) Experience with remote sensing and open-source GIS tools (e.g. Google
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. Preferred Qualifications Applicant must be a strong writer and quantitatively skilled with experience using GIS tools and statistical software, ideally R, and could have a PhD in one of several fields
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populations. Proficiency in both qualitative and quantitative research methods. Experience with R data analysis software is required (proficiency is preferred) and experience with Dedoose, Cytoscape, and/or
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, network analysis, visualization, quality control, and statistical analysis. Perform and analyze electrical neuromodulation experiments, including open-loop and closed-loop stimulation paradigms, to test
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populations. Proficiency in both qualitative and quantitative research methods. Experience with R data analysis software is required (proficiency is preferred) and experience with Dedoose, Cytoscape, and/or
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, STATA, SAS, or other statistical software; Exposure to pre and postprocessing of magnetic resonance imaging and/or magnetic resonance spectroscopy data or willingness to learn neuroimaging techniques
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Builder, and community-scale building energy tools such as UrbanOpt; advanced experience with regulatory economics modeling software may be substituted o Strong quantitative skills, with the ability
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. Experience with data analysis software (e.g., SPSS, R, NVivo) is highly desirable. Evidence of scholarly productivity, including publications in peer-reviewed journals. Strong written and verbal communication
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patients with advanced cancers (see links below for more information). These studies feature various multimodal data collection approaches, including data from surveys, biosamples, cognitive testing
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patients with advanced cancers (see links below for more information). These studies feature various multimodal data collection approaches, including data from surveys, biosamples, cognitive testing