77 parallel-programming-"Multiple"-"Simons-Foundation" Postdoctoral research jobs at University of Minnesota
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) and developing meaningful scaled score formulas and metrics. The post-doctoral associate will support multiple aspects of this work, including conceptualization and design of the scale scores, computing
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the qualification and testing of electronics for particle physics experiments. Experience in working with distributed research groups and demonstrated ability to manage multiple tasks. About the Department School
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of early writing data to new research using neuroimaging to study dyslexia. The post-doctoral associate will support multiple aspects of these projects, including conceptualization and design of new projects
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data pipelines Comply with data security guidelines Data analysis (25%) Data reduction of predictor and outcome measures Determine and implement optimal strategies for testing multiple hypotheses Utilize
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with GWAS/sequencing data and multiple types of omic/neuroimaging data, as in Mendelian randomization and TWAS. In addition to new methods development and evaluations, the job responsibilities include
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spending accounts University HSA contributions Disability and life insurance Employee wellbeing program Financial counseling services Employee Assistance Program with eight sessions of counseling at no cost
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/programming and communication skills. Essential qualifications include the ability to quickly learn new things and work independently, along with previous research experience in at least one of the following
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searching for a Postdoctoral Associate with strong research interest in behavioral medicine. The candidate will participate in an active NIH and NSF biobehavioral research program (Director, Mustafa al'Absi
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: Competitive wages, paid holidays, and generous time off Continuous learning opportunities through professional training and degree-seeking programs supported by the Regents Tuition Benefit Program Low-cost
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skills in R programming - Working knowledge of Python - Experience with basic analyses to characterize gut microbiomes, including diversity analysis, differential abundance analysis, modeling microbial and