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this area will also be considered. The ideal candidate should be proficient in scientific programming (e.g., Python or MATLAB) and have a genuine interest in developing and testing experimental setups
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and analytical skills; experience in programming, e.g., in C++, Python or Matlab (experience with programming of sofware defined radios and/or off-the-shelf communication modules is a plus); a creative
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in working with large data sets and the development of numerical models. Basic knowledge of glaciology or geodesy. Good expertise in programming, e.g. in Python, MATLAB, or other high-level programming
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(e.g. C++, Python, Matlab) OpenFOAM (beneficial, not required) Strong analytical and problem-solving skills. Approval and Enrolment The scholarship for the PhD degree is subject to academic approval, and
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project focus. Technical computing skills: Strong programming skills (e.g. Python, C++, MATLAB). Experience with robotics software frameworks such as ROS, Gazebo, or other simulation environments is
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sensors (sonar, camera, inertial units) and their limitations would benefit this project’s focus. Technical computing skills: Proficiency in programming (e.g. Python and C++). Experience with robotics
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engineering, mathematical and programming contexts Your research will include extending and contributing to models and codes, including both high- and low-level programming languages, e.g. Python/Matlab
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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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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