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Field
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Experience in teaching at undergraduate and/or advanced levels in the field is desirable. Documented expertise and working experience within at least three of the following research and educational areas is a
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. Assessment criteria Theoretical knowledge and practical experience, and methodological competence in the biological stability of natural polymers against mold, fungi, and enzymatic degradation are meritorious
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therapeutic strategies that efficiently target currently hard-to-treat ovarian carcinomas. Work responsibilities The successful applicant will independently perform animal experiments with human ovarian
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reliable and sustainable components more affordably and more efficiently. Due to the complexity of the research, an integrated framework combining experiments, simulations, and data-driven methods is
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subject area at MDU for more than one year. You must have good oral and written skills in English and experience of independently planning, conducting and reporting research in the field of higher education
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and practical experience, and methodological competence in surface characterization, surface degradation, ageing performance are meritorious. Good scientific publication rate and experience in acquiring
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targets, e.g., Kubernetes is a strong advantage. An excellent knowledge in the focused research areas of Software Technology and Machine Learning are strong advantages. Experience in teaching at
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experience in project design, analyses, interpretation and scientific publication and be involved in a project that develops future AI tools for genomic analysis. Examples of areas in which the scholarship
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. Proficiency in programming languages, compilation techniques and optimizations. Proficiency in C, C++, and/or Rust. Merits: Experience with e-graphs. Familiarity with theory and algorithms used by, for example