93 phd-energy-or-power-or-grid-or-optimization Postdoctoral positions at The Ohio State University
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to submitting your application, please review and update (if necessary) the information in your candidate profile as it will transfer to your application. Job Title: Post Doctoral Scholar - Physiology & Cell
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to submitting your application, please review and update (if necessary) the information in your candidate profile as it will transfer to your application. Job Title: Post Doctoral Scholar - Physiology & Cell
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machine learning—for chemical and biological applications. You will design and implement models ranging from molecular to process scales, develop model-predictive control and optimization strategies, run
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, biochemistry, peptide synthesis, enzymology, cell biology, and human iPSCs to explore disease mechanisms and the roles of protein kinases and PTMs (e.g., phosphorylation, ubiquitination). The candidate will
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of RNases related to human health and disease. The Post Doctoral Scholar will embark on a program of independent research with the primary goal to determine how RNases regulate gene expression in the cell
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policies, procedures, rules, and regulations. Performs other job-related assignments as assigned. Qualifications A PhD or MD/PhD, within the last three years with extensive experience cell/molecular biology
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engineering, with applications in energy systems and other natural and engineered networks. Additional Information: Hiring Salary: $61,800 Application materials should include: - Cover letter outlining your
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successful careers in academia or industry, depending on the priorities of the candidates. Qualifications: A Doctoral degree (PhD, or MD/PhD) in Biochemistry, Cell Biology, Structural biology, Biophysics
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for personalizing either Ti6Al4V, CP Ti, or SS 316 alloy fixation plates. This person will assist a HAMMER GRA implement feedback between Virtual Surgical Planning (VSP) that includes device design and optimized
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machine learning—for chemical and biological applications. You will design and implement models ranging from molecular to process scales, develop model-predictive control and optimization strategies, run