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are an interdisciplinary team spanning engineering, neuroscience, developmental biology, genetics, applied math, and physics — united by curiosity and a drive to understand how the brain coordinates whole-body physiology
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teaching load and a requirement to be involved with mentoring undergraduate students in research through the Iowa State Math Research Teams (ISMaRT, https://sites.google.com/view/ismart-iastate ). A complete
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combinatorics, extremal combinatorics, and flag algebras. The position has a 2-1 teaching load and a requirement to be involved with mentoring undergraduate students in research through the Iowa State Math
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://www.nsf.gov/awardsearch/showAward?AWD_ID=2424632 ). The position has a 2-1 teaching load and a requirement to be involved with mentoring undergraduate students in research through the Iowa State Math Research
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advantage. You should have a university degree at PhD level in the field of economic sciences, including finance and accounting, or mathematics and natural sciences, focusing on mathematics. Our team offers
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have a university degree at PhD level in the field of economic sciences. Our team offers flexible working hours and intensive cooperation in a committed team. The application deadline is December 12
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are an interdisciplinary team spanning engineering, neuroscience, developmental biology, genetics, applied math, and physics — united by curiosity and a drive to understand how the brain coordinates whole-body physiology
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are intended for young mathematicians with a strong research record. Fellows must have completed a PhD in mathematics prior to the start of their fellowship. Women are particularly encouraged to apply
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advantage. You should have a university degree at PhD level in the field of economic sciences, finance / accounting / management field , or systems engineering, computers and information technology, systems
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urban structures * Urban informatics applications for sidewalks analysis ** Candidate Qualifications: * PhD in Physics, Math, Computer Science, Engineering, or a related field. * Strong background in