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expertise in educational and social science research methods, with a strong background in quantitative and/or qualitative analysis. Show evidence of experience in survey research, instrument development, and
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discovery in cancer science, with a focus on the kidney cancer microenvironment. Develop successful manuscripts and grant applications to support all or part of the research effort. Partner with Dr. Rathmell
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for these systems. Duties will include conducting computational research work centered on developing new computational methods for simulating complex chemical and physical systems; leading manuscript preparation
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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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appropriate agencies and Institutions; identifies and selects problems to be studied; develops and troubleshoots new experimental techniques and protocols; attends research seminars; contributes to manuscript
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. Efforts to secure funding essential for successful career development will be encouraged and supported. The position will remain open until filled. Guidance by the PI will be provided to assist with
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employer, including veterans and disability. As required by Ohio Revised Code section 3345.0216, Ohio State will: educate students by means of free, open and rigorous intellectual inquiry to seek the truth
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employer, including veterans and disability. As required by Ohio Revised Code section 3345.0216, Ohio State will: educate students by means of free, open and rigorous intellectual inquiry to seek the truth
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and mechanisms of selective autophagy and lipid metabolisms in neural stem cells, microglia, and astrocytes. The lab developed novel genetically engineered mouse models to study roles of autophagy genes
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cancer, behavioral intervention development/testing, and implementation science. Responsibilities may also include participating in qualitative interviews and analyses, participating in other study design