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opportunity to engage in cutting-edge interdisciplinary research focused on Generative AI within the context of construction robotics, working under the guidance of Dr. Arash Adel, Assistant Professor in
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but not required. Excellent writing ability in English is essential as well as creativity, energy, and the desire to work in an interactive and inter-disciplinary environment. The Term of appointment is
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Postdoctoral Research Associate - Improving Sea Ice and Coupled Climate Models with Machine Learning
learning. Our previous work has demonstrated that neural networks can skillfully predict sea ice data assimilation increments, which represent structural model errors (https://doi.org/10.1029/2023MS003757
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research levels in the areas of biochemistry, biophysics, cell biology, structural biology, microbiology, developmental biology, virology, genetics and cancer biology. The term of appointment is based
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: (i) measurements of surface composition, structure, and thermal stability using AES, LEIS, XPS, and vibrational spectroscopy; (ii) quantitative determination of the flux and fluence of incident atoms
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experiments and methods. Additional expertise in plasma, plasma-materials interactions, and/or ALE is of significant value. Experience with the design, construction, operation, and maintenance of UHV
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. Some experience with first-principle methods (FP/DFT) and/or other forms of electronic and magnetic structure theory and calculations is also expected. The successful candidate will have a strong
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of researchers Preferred Qualifications: *Experience with macroeconomic or structural modeling. Specific experience with CGE models and the use of GTAP a plus. *ArcGIS software or equivalent Requirements
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are required to have a Ph.D. or equivalent in biology, ecology or related fields. Excellent writing ability in English is essential as well as creativity, energy, and the desire to work in an interactive and
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team members to identify and examine existing theoretical models of infectious disease transmission and then develop novel theoretical models that account for structural drivers of infection