491 programming-languages-"the"-"CNRS"-"U"-"UCL"-"O.P"-"IDAEA-CSIC" positions in Denmark
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. Research-based teaching in GNSS, geodesy, and surveying. The teaching must be conducted in Danish and English at bachelor’s (BSc) and master’s level (MSc) Co-supervision of BSc, MSc, and PhD projects Public
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good insight in applications of photonic nanostructures. Have a track record of secured research funding. You must be responsible for the teaching of courses. DTU employs two working languages: Danish
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using the link “Apply now” - see below. We strongly recommend that you read How to apply for a position at SDU before you apply. Only applications written in English will be accepted for evaluation
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Research Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description Postdoctoral Position in Probabilistic Machine Learning
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English, both written and spoken. A curiosity-driven mindset and enthusiasm for developing and applying cutting-edge technologies to address biomedical questions. A proactive attitude towards learning and
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programme. Academic staff contribute to the teaching. English is the preferred language in the laboratory, at meetings and at seminars. The department employs approx. 500 people from all over the world, and
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for tomography reconstruction and analysis. To perform these tasks, we expect you to have: A strong background in X-ray tomography (synchrotron or lab-based) or other 3D imaging techniques. Solid programming
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to both experts and non-specialists. Proficiency in English is required. You must be compliant with MSCA mobility rule: not have resided or carried out your main activity (work/study) in Denmark for more
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estimation. Performing experiments to investigate synthetic samples, field samples, and samples from other projects in the program. This will require a well-established connection to other projects. Co
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are internationals. In total, it has more than 600 students in its BSc and MSc programs, which are based on AAU's problem-based learning model. The department leverages its unique research infrastructure and lab