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PhD Position - Operando X-ray Characterization of Catalytic Interfaces for Chemical Hydrogen Storage
data and, where useful, complementary methods such as microscopy, X-ray scattering/reflection, vibrational spectroscopy, or modelling. Prepare beamtime proposals, publish results in peer-reviewed
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combines high-throughput screening, directed evolution, and single-molecule biophysical methods, and spans projects from fundamental protein science to translational applications. Project background
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, indicators and survey information. The division combines macroeconometric modelling with data science methods for nowcasting, high-frequency indicators construction, machine learning, time series
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. You will be a dynamic, creative, and motivated scientist interested in pursuing questions deeply. You will use a range of methods for next generation RNA sequencing, and to integrate data from
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undergraduates from a range of academic backgrounds, including students with no prior computing experience, is highly desirable. About STIA Drawing on Georgetown's expertise across international affairs
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-relevant questions. We work with macroeconomic, microeconomic, firm-level, household, geospatial and international datasets and apply modern econometric methods, including panel-data, time-series and causal
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regions. Job description The research focuses on investigating/developing generic methods and algorithms in the context of multi-modal synthetic aperture radar (SAR) for the estimation of environmental
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chains. In this context, the successful candidate will conduct doctoral research using quantitative and qualitative research methods, including engagement with industry partners and analysis of secondary
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; conducts research to characterize the genetic basis of human cancers; develops, adopts and implements new laboratory methods to achieve characterization of the genetic basis of human cancers
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project aims to develop new methods for estimating blood pressure and quantifying flow inefficiencies using medical imaging, machine learning, and computational modelling. The doctoral candidate will