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- NTNU - Norwegian University of Science and Technology
- NTNU Norwegian University of Science and Technology
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Field
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Python) Mathematics Knowledge of these needs to be documented, and GPA (grade point average) and translation rules for the European Standardized Character System must follow the application. Moreover
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imperative, both orally and written. Documented experience with scientific programming (e.g. Python, Matlab, R; any history of activity on GitHub) as well as computational or statistical methods for data
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skills (Python preferred). Familiarity with ML/Data Science frameworks: PyTorch, JAX, Hydra, MLflow, Pandas (or similar). Additional qualifications Experience with project management, planning and
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the starting date of the position. Demonstrated competencies and skills within programming and statistical analyses (e.g., in Python, R, etc) are a requirement. A background in media technology & AI is a
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of the position. Demonstrated competencies and skills within programming and statistical analyses (e.g., in Python, R, etc) are a requirement. A background in media technology & AI is a requirement, and knowledge
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selection criteria Strong skills in relevant programming languages, particularly Python and C++, good knowledge in ROS (Robot Operating System) is an advantage, and best practice in data management and use
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selection criteria Strong skills in relevant programming languages, particularly Python and C++, good knowledge in ROS (Robot Operating System) is an advantage, and best practice in data management and use
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within programming and statistical analyses (e.g., in Python, R, etc) are a requirement. A background in media technology & AI is a requirement, and knowledge in the centre’s research areas. The applicant
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private computations. Advanced programming skills, preferably experience with programming in Python. Ability to perform research in a cross-disciplinary environment. SE NOTE: For detailed information about
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, Atmospheric Science, Environmental Science, or related fields Good knowledge and skills in statistics and programming (e.g. R or Python) is required Experience with data analysis related to terrestrial ecology