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National Research Council Canada | National Capital Region Almonte, Ontario | Canada | about 7 hours ago
Research Council Office across Canada Classification: RO/RCO Tenure: Term Work Arrangements: Depending on the nature of the work and operational requirements, positions hired through this program may be
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Course location Gießen Description/content The GGL provides an interdisciplinary, concisely structured graduate programme for all Life Science disciplines at the Justus Liebig University (JLU) in
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of microalgal biomass. The PhD student will join the Life Cycle Sustainability (LCS) group and will collaborate with other international research partners. LCS brings together multiple competences within
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Sarah Kate Bearman). (2) NAMI-funded pilot study of flexible mental health literacy program for middle school students (PIs Sarah Kate Bearman and Molly Lopez (UT Austin)). (3) Foundation-funded
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seeking a motivated Researcher 2 to join our team. This position is critical to CFAES’s research and Extension mission, supporting projects such as the Overholt Drainage Education and Research Program, the
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Programme duration 6 semesters Beginning Only for doctoral programmes: any time Tuition fees per semester in EUR None Combined Master's degree / PhD programme No Joint degree / double degree programme No
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programs, the university unites the natural and engineering sciences with the humanities, social sciences and medicine. This wide range of disciplines is a special feature, facilitating interdisciplinarity
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, and transport sectors (RENEW) Strong skills in implementing convex, linear, and mixed-integer programming and modelling frameworks (JuMP, Pyomo, Yalmip, GAMS, etc) Experience of working with future
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shadows Strong mathematical education, in particular in relation to linear algebra Programming experience is a plus Ability to effectively communicate in written and spoken English Ability to work
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hardware. Relevant programming experience developing, implementing, debugging, and maintaining applications with Python. Experience training ML models using large-scale and specialized hardware. Experience