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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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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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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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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: https://www.math.aau.dk/english. Stipend 2 will be located at the Department of Health Science and Technology, that conducts research that spans biomedical sciences, clinical research, biostatistics
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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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on different aspects of AI, with main focus on visual data. You may read more about VAP Lab, including current projects and members, here: https://vap.aau.dk/ The candidate will also be part of the Pioneer
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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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recruitment process at https://employment.ku.dk/faculty/recruitment-process/ . Questions For specific information about the PhD fellowship, please contact Shingo Kono (shingo.kono@nbi.ku.dk). General