39 python-"Multiple" "NTNU Norwegian University of Science and Technology" PhD positions in Denmark
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prior experience in at least three of the following areas: Python programming Develop LLM-based tools to automate data connector generation for data ingestion. Design and implement a multi-layered storage
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proficient in ROS/ROS2, Python and/or C++/C# Knowledge and/or experience within one or more of the fields of acoustic sensing, hydrodynamics, and machine learning is a plus. You have strong communication
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areas: Scientific programming using Python Data analytics and machine learning techniques Wind energy systems, operations, or related topics In addition, you should be able to work efficiently as part of
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areas: Knowledge of computer science and operations research Familiarity with renewable energy systems and their challenges Proficiency in programming languages such as Python or Julia Strong problem
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part of the Perception and Cognition for Autonomous Systems Group (PCAS), and you will find yourself among multiple PhD students and senior researchers working on multiple aspects of autonomous robotics
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Experience with Fortran, Python and Linux Shell Experience working with large datasets Preferred but not essential: Knowledge of wind farm parameterizations in mesoscale models Experience in the field of wave
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equivalent to a two-year master's degree. Additional qualifications include: Good programming skills in Python, Julia, R or similar, and familiarity with C, C# or C++. Curiosity and interest in future urban
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with multiple people working on similar problems with different professional and cultural backgrounds. You are therefore a talented, self-motivated, and team-oriented person who enjoys working
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spectrometry, and untargeted data science workflows. Proficiency in chemometric methods and/or python programming will be an advantage. Candidates are expected to be enthusiastic and adaptable to working in
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development and marine management. Your primary tasks will be to: Compile and harmonize data from multiple sources (e.g., EMODnet, Copernicus, fisheries surveys, citizen science). Engage with data managers and