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; measurement system characterization, e.g., validating platform performance such as dynamic range, linearity, phase noise and measurement uncertainty; automated test & data acquisition, e.g., using Python/MATLAB
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and analytical skills, including quantum theory, materials science and physical modelling Experience in programming, e.g., in Python or Matlab. Experience with quantum simulators, such as NetSquid, is a
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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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communication. Strong competences in mathematical modelling and simulation of flow, heat transfer and dynamic system behaviour, including use of tools such as MATLAB/Python and CFD. Strong hands-on experience
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, including signal processing, optimization, machine learning or information theory; Experience in programming, e.g., in C++, Python or Matlab. Qualification requirements PhD stipends are allocated
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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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. Expertise with the following engineering tools and programming languages can be an advantage but not limited to: MATLAB, PLECS, PSCAD, others. Excellent English language skills (both oral and written
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can be an advantage but not limited to: MATLAB, PLECS, PSCAD, others. Excellent English language skills (both oral and written). Publications in international journals/conferences will be valued
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skills, Experience in programming in Python or another language, e.g., in C++, Matlab, R, Familiarity with basic concepts of dynamical systems, Knowledge of wind turbine dynamics is a plus, Curiosity to
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Python and/or Matlab. Experience with software-defined communication systems, emulation tools, and machine learning techniques is considered an advantage. Most importantly, you are eager to learn and apply