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proficiency in scientific programming (e.g. in python) and must demonstrate the ability to handle large amounts of data confidently and systematically. Previous experience with machine/deep learning will be
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. The candidate should ideally have experience or interest in one or several of the following areas: A solid foundation in programming and system development, particularly using Python and machine learning
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learning, data science, atmospheric sciences, geophysics, or related fields. Solid numerical modelling and programming skills (e.g., Python, TensorFlow, scikit learn) are essential, along with a basic
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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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, 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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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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data science. You must be curious and driven with excellent interpersonal skills and writing competencies. Experience with programming languages, notably Python or R, is expected. The work will imply
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, Python and/or R, and ability to manage and structure large datasets is essential. Interest/skills in application of AI methods to clinical data is an advantage. Stipend 2: Genetic Risk Communication and
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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