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SFI FAST: PhD position in Microstructure/texture evolution during extrusion of scrap-based Aluminium
of deformation mechanisms and recrystallization processes. The project will focus on understanding and modelling the microstructure evolution during extrusion, with particular emphasis on crystallographic texture
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the candidate is the lead author; • experience in working with cells in 2D and 3D models, including radiobiological methods; • experience in working with mouse tumor models and in imaging small laboratory
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in France is crucial to inform risk analysis and mathematical modelling, and obtain precious information for epidemic preparedness, particularly for outdoor farming systems which are highly prevalent
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modelling, sustainability, and energy economics. Applicants should hold a master’s degree with very good grades in mechanical engineering, energy engineering, or a closely related field. Fluent written and
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dependent educational benefits Life insurance coverage Employee discounts programs For detailed information on benefits and eligibility, please visit: http://uhr.rutgers.edu/benefits/benefits-overview
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, or related fields Foreign completed degree (M.Sc.-level) corresponding to a minimum of four years in the Norwegian educational system Fluent oral and written communication skills in English Desired
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that you are particularly suitable for a PhD education. You must meet the requirements for admission to the faculty's Doctoral Programme (https://www.ntnu.edu/studies/phiv ) You must be fluent in spoken
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for users of the Monarch Android pin‑array tablet (https://www.humanware.com/en-usa/monarch ). In this role, you will work closely with Humanware’s ML developers to design and implement an ML toolchain
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, Aquaculture, or equivalent; 2. Fluent in English in writing and speaking; 3. Experience in macroalgae culture maintenance/methodology and sporulation techniques; 4. Experience with seaweed farming in
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, for the project/R&D institution “SoftEdIBO – Soft-based robot for inclusive education”, “2024.15729.PEX”, “DOI: https://doi.org/10.54499/2024.15729.PEX ”, funded by the Fundação para a Ciência e a Tecnologia, I.P