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to evolve classical communication networks to support both traditional data and the unique requirements of quantum information systems (https://www.classique.aau.dk). CLASSIQUE will address a suite of
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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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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
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Engineering, Machine Learning, Artificial Intelligence, Computational Linguistics, or a related field) • Strong programming skills (e.g., Python) • Strong skills in machine learning, deep learning and modern
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at least one scientific programming environment such as Python, MATLAB, or R. Familiarity with structural degradation phenomena—including fatigue, corrosion, and biofouling—would also be beneficial
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Python (or equivalent). Experience with glass science, battery materials and/or atomistic simulations is highly advantageous. All interested candidates are encouraged to apply, regardless of their personal