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of the grant: Jacinto Paulo Simões Estima; Catarina Helena Branco Simões da Silva IV - Work Plan / Goals to be achieved: Title: Automatic Container Recognition in Dry Ports Summary description
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University of California, San Francisco | San Francisco, California | United States | about 1 month ago
for this position is $78,900 - $167,300 (Annual Rate). To learn more about the benefits of working at UCSF, including total compensation, please visit: https://ucnet.universityofcalifornia.edu/compensation-and
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or international recognition in printmaking/drawing and/or emergent practices of design. Discipline Specific Required Qualifications Robust knowledge of technique, theory, and history of printmaking. Familiarity
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to contribute to developing the next generation of risk-informed design methodologies for infrastructure exposed to natural hazards and climate change. About the project Infrastructure systems such as roads
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including but not limited to nutrition, behavior, or Individual Family Service Plans. Early Head Start teachers work in teaching teams of two or three in conjunction with the Education Director to design the
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Laboratory for Sustainable Chemistry within the School of Chemistry at the University of Nottingham. The successful applicant will design and synthesise new organocatalysts and explore their application in
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whether these tools improve human accuracy, how they affect machine recognition, and whether they introduce demographic biases. This interdisciplinary PhD will investigate how generative AI–based super
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at an international level successfully passed an evaluation of six-years of research period at AQU (private universities) or ANECA: https://www.aqu.cat/en/teaching-staff/Assessment-and-recognition-of-merits/Avaluacio
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obtained overseas for which the relevant official approval, statement of comparability or recognition has not been secured by the application deadline, the applicant will be required to present evidence that
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experimental approaches to design and characterize ligand-binding proteins. We develop machine-learning techniques to compute the structures and sequences of proteins that bind to challenging small-molecule