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., in C++, Python or Matlab. Who we are The successful candidate will be hosted by the Section on AI & Sound. This section is led by Prof. Jan Østergaard. A dedicated supervisory team composed of experts
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computational scientific workflows. Experience with scientific programming (Python or similar) Experience working in Linux-based computational environments Documented experience with high-performance computing
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programming, e.g., in C++, Python or Matlab. Who we are The successful candidate will be hosted by the Section on AI & Sound. This section is led by Prof. Jan Østergaard. A dedicated supervisory team composed
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acceleration. Strong programming (C/C++/Python), data structures and software development skills. Track record of research excellence through publications or public repositories Good communications skills
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discipline prior to enrolment. The successful candidate should demonstrate: Strong programming skills (e.g. Python, C++ or similar) Solid foundation in linear algebra, geometry, and optimisation Experience
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, or cybersecurity principles. Familiarity with signal processing, particularly with high-frequency sensor data (such as acoustics or vibration) is an advantage. Programming skills: You are proficient in Python
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experimental fluid mechanics Enthusiasm, creativity, and a can-do attitude Programming skills (Ideally PALM-4U, Python / MATLAB or similar) Excellent communication skills in English (both spoken and written) You
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communications, fundamental knowledge on computing architectures, and advanced programming skills (e.g., Python, C++, Matlab/Octave). Experience with simulation, emulation, and modelling tools for signal
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materials chemistry and excellent analytical skills. Proficiency in scientific programming (e.g. in python). Excellent oral and written English language skills. Strong collaborative skills, team spirit and
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modeling Programming/scripting skills (e.g., Python, R) for data handling and visualization Strong interpersonal and cross-disciplinary collaboration skills What We Offer Innovative Research Framework