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/Natural Resources Internal Number: 1121375 Position Summary The Michigan State University Department of Energy Plant Reseach Lab (MSU DOE-PRL) for a Postdoctoral Associate in research on plant endomembranes
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based in the Department of Supply Chain Management. The successful candidate will contribute to research at the intersection of people-centric operations, social sustainability, analytical modeling, and
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: Computational, Quantitative, and Predictive Modeling of Root Systems. This position emphasizes integration of phenomics and other -omics data into predictive frameworks. Research areas may include: Structural
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management, and enhance ecosystem services outcomes. The researcher will also have ample opportunity to collaborate on complementary projects focused on mapping, modeling, and advancing agricultural
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research experience, career goals, motivation to join the Hsu lab & potential start date, 2) CV, and 3) contact information of three professional references. Website https://sites.google.com/view/polly-hsu
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, chemotherapy, formaldehyde, asbestos, etc. Trastuzumab-deruxtecan, chemotherapeutic Work with animals or unfixed animal tissue Website https://bmb.natsci.msu.edu/ MSU Statement Michigan State University has been
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: 1116179 Position Summary Successful candidates are expected to work on molecular design and theoretical modeling of soft materials as well as their applications in healthcare and sustainability
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, religion, sex, sexual orientation, gender identity, national origin, citizenship, age, disability or protected veteran status. Required Degree Doctorate -molecular biology, biochemistry, cell biology
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on advanced internal combustion engines, with an emphasis on turbulent-jet ignition systems and structural-mechanics modeling of cylinder-kit components. The ideal candidate will possess a strong background in
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developing data acquisition and signal processing software (LabVIEW, MATLAB, etc.), mainly for temperature and pressure data. Some familiarity with magnetic fusion energy Required Application Materials CV