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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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to damage detection, condition monitoring, and forecasting. You are proficient in Linux and Python, preferably with experience in PyTorch or a similar deep learning framework, and you are able to design 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
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, or Python. You will also be able to shape your own research. This includes primary data collection through surveys, or qualitative or quantitative interviews. Working as a PhD student requires the ability
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knowledge and skills in machine learning - Significant experience in programming, e.g., in C++, Python or Matlab. Experience with quantum simulators, such as NetSquid, is a plus; - Familiarity with the
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candidate is expected to hold: A master degree in biomedical engineering or computer science, Excellent programming skills (Python). Experience with data curation, large-scale datasets, and machine learning
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, material processing, and/or atomistic simulations is an advantage. Excellent analytical skills and proficiency in scientific programming (e.g. in python) are an advantage. Excellent oral and written