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for publication in high-impact journals and conferences; Create, maintain, and document high-quality research code for reproducibility; and Collaborate with scientists within the NYU Global Network and in Abu Dhabi
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of manuscripts for publication in high-impact journals and conferences; Create, maintain, and document high-quality research code for reproducibility; and Collaborate with scientists within the NYU Global Network
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experience with the Adult Attachment Interview, the Attachment Script Assessment, or narrative coding/natural language processing are encouraged to apply. Further, statistical expertise in structural equation
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, programming and coding (preferably using Python and C++) along with GUI and simple computational tool development. The candidates will work in a multidisciplinary environment consisting of PhD-level scientists
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developing economies. We seek a candidate with expertise in both empirical and theoretical economics, with good coding skills. The role will involve designing surveys, working with existing datasets, and
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-quality research code for reproducibility; and Collaborate with scientists within the NYU Global Network and in Abu Dhabi. Minimum Qualifications Currently has a Doctoral degree from a recognized
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structural level), 3D printing and physical modeling for structural and geotechnical application, programming and coding (preferably using Python and C++) along with GUI and simple computational tool
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models featuring rich input-output linkages. The ideal candidate should have practical experience and proficiency in handling large datasets and coding sophisticated simulations and estimations
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empirical and theoretical economics, with good coding skills. The role will involve designing surveys, working with existing datasets, and applying structural models relating to human capital development and
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machine learning algorithms (e.g. regression, neural networks). Utilizing the following programming languages/frameworks: bash, SQL, Python, HTML, Javascript, and Tensorflow/Pytorch, as well as code version