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) Position Description: Apply Position Description Faculty Position Available Focus: Site Assembly and Landscape Design Studio Department of Landscape Architecture, Cornell University Position
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conditions: Scientific Area: Product Design or related areas Recipients: Masters in Industrial Design, Product Design or related areas, enrolled in a PhD or non-degree course, in the scientific areas indicated
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(January 25). The presentation of the recognition certificate is mandatory for contract signature. More information can be obtained at: https://www.dges.gov.pt/en/pagina/degree-and-diploma-recognition
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composition, dance history, world dance, aesthetics, pedagogy, music theory, dance science (kinesiology, injury prevention, Pilates), dance production, stage management, lighting and scenic design, costume
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at Carnegie Mellon University More Jobs from This Employer https://main.hercjobs.org/jobs/21808208/assistant-or-associate-professor-x28-tenure-track-x29-in-architectural-design Return to Search Results
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process, particle structure and product performance will be developed, and there will be opportunity to create new process design and scale-up tools for these processes. Main duties and responsibilities
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Fundacion para la Investigacion e Innovacion Biosanitaria de Atencion Primaria | Spain | 20 days ago
of the contract is to collaborate in the lines of work and implementation of the project, developing the following functions: Design and implementation of ETL flows for the integration, transformation and loading
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of Fine Art, Music and Design (KMD), there is a vacant position as PhD Research Fellow (100%) in Artistic Research connected to the newly formed MishMash Centre for AI and Creativity. The position is for a
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environment to grow and groom future business leaders. And we are looking to add to our BIZ family! To learn more about the NUS Business School, please visit https://bschool.nus.edu.sg/ Job Description Core
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. Machine Learning and Artificial Intelligence: Experience in applying ML and AI techniques to engineering. This includes data-driven modeling, pattern recognition, predictive maintenance, and intelligent