12 evolution "https:" "https:" "https:" "https:" "https:" "https:" "UCL" uni jobs at University of Aveiro
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of the assessment described under Section 5 below. 2.3 — The compulsory application minute, to be completely filled out, dated, and signed, is available at https://www.ua.pt/file/78384 . 2.4 — Submission
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Full Professor, explaining how one can contribute to the progress and development of the field of Optics in the technical-scientific, pedagogical, and cooperation with society aspects; f) Document
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proposal of activities that the candidate intends to develop during the first five years of your activity as an Assistant Professor, explaining how you can contribute to the progress and development
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the candidate intends to develop during the first five years of your activity as an Assistant Professor, explaining how you can contribute to the progress and development of the subject area to its open the
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panels based on a new LSF profile concept. This profile will enable the production of double-cloth panels, which offer high performance and low environmental impact. The development of an assembly system
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, construction, and assembly processes, adaptable to different building typologies. Accordingly, the work plan includes: 1) Development of experimental tests and numerical simulations of slotted LSF profiles
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of the assessment described under Section 5 below. 2.3 — The compulsory application minute, to be completely filled out, dated, and signed, is available at https://www.ua.pt/file/78384 . 2.4 — Submission
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Aveiro City Aveiro Website https://www.ua.pt/pt/decivil Street Campus Universitário de Santiago Postal Code 3830-193 E-Mail romvic@ua.pt STATUS: EXPIRED X (formerly Twitter) Facebook LinkedIn Whatsapp More
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: Experience: in numerical modelling applied to the study of sediment dynamics and coastal morphodynamics; in the production/publication of scientific papers and technical reports; in the development of projects
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Grant(s) (RG) in the scope of R&D projects FireLSF - Development of predictive models for the fire resistance of light steel frame walls - an integrated experimental, numerical and machine learning