588 machine-learning-"https:" "https:" "https:" "https:" "https:" "https:" "University of Waterloo" positions in Norway
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during the employment period. A career development plan will be drawn up, outlining the competencies the Postdoctoral Fellow is expected to acquire during the employment period. The Postdoctoral Fellow
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and/or supervision duties. Postdoctoral fellows who are appointed for a period of four years are expected to acquire basic pedagogical competency in the course of their fellowship period within the duty
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future career. A career plan shall be developed for the Postdoctoral Fellow, specifying the competencies the Postdoctoral Fellow should acquire. UiO is responsible for following up on the career plan and
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will arrange for you to acquire such competence during the employment period. In such cases, you will also be assigned relevant teaching as part of the career-promoting work. The appointment is to be
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competence and experience, including a reflection note in which your own practice and learning vision is anchored in the SoTL criteria described as keeping a focus on student learning, students’ development
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critically and will work both independently and collaboratively within the project consortium. You should enjoy interdisciplinary research and take keen interest in learning and working as part of
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developed for the Postdoctoral Fellow, specifying the competencies the Postdoctoral Fellow should acquire. UiO is responsible for following up on the career plan and ensuring that the Postdoctoral Fellow has
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the Postdoctoral Fellow should acquire. UiO is responsible for following up on the career plan and ensuring that the Postdoctoral Fellow has access to career guidance throughout the postdoctoral term
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both NMBU and NTNU. The applicant must have an academically relevant education corresponding to a five-year master’s degree, with a learning outcome corresponding to the descriptions in the Norwegian
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in English Solid knowledge in finite element analysis (FEA) and strong skills in FEA software such as ABAQUS Hands-on experience in the construction and application of deep learning neural networks