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planetary boundaries (a set of at least nine parameters that indicate how far the ES is from its optimal functioning state during the Holocene (about 12,000 years ago). This model is inspired by Matrix Models
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Design and Manufacturing Engineering to Tackle Global Sanitation Challenges - MSc by Research or PhD
for engineers who can seamlessly integrate design optimization with advanced manufacturing techniques. This multidisciplinary field combines mechanical engineering, materials science, and manufacturing technology
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systems for process optimization. (1 to 5 points). D. Motivation letter that will allow to evaluate the English proficiency and motivation of the candidate (1 to 5 points) After reviewing the submitted
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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
Optimization of part design based on computational technologies Manufacturing of proof-of-concept parts using AI-optimized parameters for iSLS Post-processing of proof-of-concept parts Participation in
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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
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requirements: Candidates should possess expertise in the characterization of nutrients and bioactive compounds derived from undervalued resources and food products. Experience in optimizing extraction processes
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; consistent messaging; customer service; and processing. Extensively collaborates with FAS staff leadership on best practices, policies and business process development, optimization, maintenance, and
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agriculture. iii) Definition of a technological maturity model to determine the most suitable digital technologies to improve and optimize olive production, including the definition of key indicators. iv
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based on deviations from expected operating conditions or optimization of operational parameters. iv) Development of a user interface for data visualization and recommendations, allowing the user
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-vision algorithms with edge-computing processing for the automatic detection of non-conformities. Machine-learning techniques will be applied to optimize cutting parameters, and the module will be