25 analog-and-integrated-circuits Postdoctoral research jobs at University of Minnesota
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Previous Job Job Title Post-Doctoral Associate - Department of Integrative Biology and Physiology Next Job Apply for Job Job ID 368521 Location Twin Cities Job Family Academic Full/Part Time Full
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focus on superconductor, semiconductor or hybrid semiconductor-superconductor quantum electronic devices, and microwave approaches applied to quantum circuits. About the Department School of Physics and
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Job Code 9546 Employee Class Acad Prof and Admin Add to My Favorite Jobs Email this Job About the Job Research This research is related to the integration of computation into the undergraduate physics
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Responsibilities This position will work to improve greenhouse gas emissions estimates for dairy farming systems. The candidate will be responsible for developing whole-farm analyses which integrate soil trace gas
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-electronics, Optics and opto-electronics, Signals and image processing, Systems and controls, and Very large scale integration (VLSI). Pay and Benefits Pay Range: $61,008 - $71,008; depending on education
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, the researcher will integrate -omics approaches and geochemical assays to shed light on fungal-selenium interactions. This work has direct application to contaminant bioremediation as well as understanding
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for generalized additive mixed-effects models Design analysis pipelines that integrate behavioral and physiological data streams. Presentation/Dissemination of Findings (40%) Write scholarly manuscripts describing
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Council, the project will integrate new data collections with existing datasets from recent studies and monitoring programs to understand how pond age, design and management influence trajectories of pond
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data integration - A record of publication in peer reviewed journals - The ability to meet strict deadlines. Pay and Benefits Pay Range:$65,000-80,000 annually ; depending on NIH Stipend levels and
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on applying, developing and implementing novel statistical and computational methods for integrative data analysis, causal inference, and machine/deep learning with GWAS/sequencing data and other types of omic