52 phd-mathematical-modelling Postdoctoral positions at Pennsylvania State University
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to investigate iconicity in spoken language – the idea that the sound of a word may convey its meaning – in both neurotypical people and people with aphasia. The successful candidate will have a PhD in a relevant
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functional magnetic resonance imaging: fMRI) methods to investigate iconicity in spoken language – the idea that the sound of a word may convey its meaning. The successful candidate will have a PhD in a
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resonance spectroscopy applied to investigate post-translational modifications of intrinsically disordered proteins. The position requires a PhD in chemistry with a focus on spectroscopy applied
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project management. This position requires a PhD in nematology (preferred), forestry, plant pathology, microbiology, microbial ecology, or a related field. Competitive candidates must have significant
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for metric-valued (including functions, distributions) data analysis, optimal transport and gradient flows, and deep learning. A Ph.D. in Statistics, Mathematics, CS/EE (with a focus on statistics/machine
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, Mathematics, or a closely related field. For full consideration applicants must complete the Penn State application and must submit the following materials by May 15th. • A research statement. • Curriculum
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mentoring of graduate students. The required qualifications are: PhD degree in Civil Engineering, Materials Science, Chemical Engineering, or related field Extensive research experience related to concrete
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, self-driven, collaborative, skilled young microscopist with a PhD in materials science, physics, chemistry, or a related field that has a thorough background in aberration-corrected scanning/transmission
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presentation at conferences and manuscript preparation Specific criteria include: Recent MD or PhD (0 - 3 years) in a relevant biological science or bioengineering discipline Strong critical thinking skills
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research involving biological data analysis and modeling of biological systems. In particular, they will develop and apply algorithms to construct discrete dynamic models of signal transduction networks