81 programming-language-"University-of-Oslo" research jobs at Technical University of Denmark in Denmark
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European level Participation in teaching activities Teaching and Learning education You must contribute to the teaching of courses. DTU employs two working languages: Danish and English. You are expected
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airborne geophysical observations, and strong competences in Arctic fieldwork logistics. The gravity research group has carried out airborne gravimetry since the 1990s and has an annual work programme to
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computational chemistry or physics will be preferred, but candidates with a solid background in statistics, computer science, and/or mathematics are also encouraged to apply. Programming skills (e.g., Python
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you are open to working with other colleagues. Qualifications You can work independently, plan and execute complicated and challenging tasks. You are flexible, self-motivated, interested in
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of microbial biogeochemistry Proficiency in scientific programming and data analysis using tools such as Python, R, MATLAB, or similar Excellent written and verbal communication skills in English
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. Knowledge of compilers, especially an LLVM-based compiler tool chain, program analysis, and computer architecture. Knowledge of real-time systems. Systems programming and C/C++. We offer DTU is a leading
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Solid programming experience, preferably in Python Familiarity with structured data handling (e.g., SQL) and scientific workflows Documented experience with ontology development, knowledge graphs, and
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documented prior experience with either biosynthesis or electrochemistry, or both. The ideal candidate is a good communicator in both written and spoken English, is independent, and enjoys collaborating with
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language models (LLMs) for educational purposes. Furthermore, the right candidate has a deep understanding of pedagogical research, with focus on how educational processes can be facilitated by AI. The role
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, TESPy, or similar libraries. Strong programming skills in Python or MATLAB, including use of scientific libraries (e.g., NumPy, Pandas, Matplotlib, etc). Experience with machine learning (e.g., Scikit