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Nonfiction Writing. A PhD in English, Rhetoric and Composition, or a related field is required. Candidates must have prior teaching experience. Preference will be given to candidates with experience in dual
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full-time basis. Preferred Qualifications: Demonstrated knowledge of composition theory and pedagogy. Interest and experience in multiple levels of composition, including developmental and honors
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parameters shall be given the following percentage weighting: 0,2 x A + 0,3 x B + 0,5 x C. Composition of the selection panel:Inês Nunes de Sousa Soares (PhD; Chairman). Luís Filipe Caeiro Margalho Guerra
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Website https://www.academictransfer.com/en/jobs/357989/add-ream-3-phd-positions/apply/ Requirements Specific Requirements A Master’s degree in Mechanical Engineering, Materials Science, Industrial
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will be immediately recruiting a motivated graduate (master’s/PhD) student to start as early as Summer 2026. The selected candidate will work on a funded research project focused on developing novel
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in polymer, composites, or soft-matter modelling, scientific programming, and machine-learning-supported optimisation is an advantage. PhD Position 3 – Computational–Experimental Integration This PhD
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PhD Studentship in: Food Waste to Sewer: Evidence, Infrastructure Resilience, Circular Economy and Policy Implications School of Mechanical, Aerospace and Civil Engineering PhD Research Project
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the kinetics of the relevant redox reactions on multiple electrode surfaces to unravel the relationship between chemical composition and performance, using a wide variety of electrochemical and analytical
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Associação do Instituto Superior Técnico para a Investigação e Desenvolvimento _IST-ID | Portugal | about 1 month ago
: Comparative Analysis - Apply multiple analytical perspectives to critically examine the collected materials. Phase 3: Model & Method Development - Map findings onto established design processes and propose a
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SD- 26053 PHD IN ULTRA-FAST MACHINE-LEARNING INTERATOMIC POTENTIALS FOR NANOINDENTATION OF TIC MA...
PhD candidate to develop and apply ultra-fast machine-learning interatomic potentials (UFPs, Xie et al., npj Comput. Mater., 2023, 10.1038/s41524-023-01092-7 ) for long, multi-million-atom molecular