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This opportunity adds to the portfolio of projects within the new CDT for Innovation for Sustainable Composites Engineering launched in 2024: https://www.bristol.ac.uk/composites
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Engineering, or related scientific fields; - Suitability of the candidate's training and experience to the objectives of the work to be developed; - Possess relevant experience in automation, Industry 4.0
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This opportunity adds to the portfolio of projects within the new CDT for Innovation for Sustainable Composites Engineering launched in 2024: https://www.bristol.ac.uk/composites
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the framework of STAMP-IT Project, 18405 - COMPETE2030-FEDER-0147390, financed by Portugal 2030, under the following conditions: Scientific Area: Manufacturing and Industrial Management Admission Requirements: be
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the scope of the following project tasks: - Sustainable manufacturing of aerogels from rPET (dissolution/precipitation of rPET with green solvents; optimization of rPET aerogel production by DoE); - Expansion
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Helmholtz-Zentrum Dresden-Rossendorf - HZDR - Helmholtz Association | Dresden, Sachsen | Germany | 3 months ago
employment. Starting date: 01.12.2025 Job description:PhD Student (f/m/d) in Ion Irradiation and Materials Characterization of Novel Additively Manufactured Materials for Fusion Applications With cutting-edge
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learning and living environment and scientific research and innovation conditions with its first-class teaching and laboratory environment, complete living facilities and a pleasant campus ecology. https
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properties of the different protein extracts, with particular emphasis on properties relevant to the food industry, namely emulsifying capacity and bioactivities. iii) To investigate the interaction
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special emphasis on pharmaceuticals, in aqueous samples; ii) Experience preparing activated carbon or biochar from food industry waste; iii) Experience functionalizing activated carbon or biochar. (View
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Escola Superior de Design, Gestão e Tecnologias da Produção de Aveiro - Norte da Universidade de Aveiro | Portugal | about 2 months ago
Regulations of the University of Aveiro. 5. Work Plan: This project aims to develop solutions based on Artificial Intelligence for optimizing additive manufacturing processes. Machine learning techniques will