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growth and yield studies. Knowledge of different digital data collection tools, statistical approaches, machine learning and AI-based techniques, forest growth modelling and simulation systems, as
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ownership of open-ended problems The following are seen as advanteges but not necessary: Experience working with unstructured data sources (e.g. documents, long-form text) Familiarity with machine learning
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establish independent research groups at FIMM and contribute to the development and application of cutting-edge statistical and machine learning methods in molecular medicine and population health. This group
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data library Apply diverse data science and machine learning methodologies, including the development of novel analytical approaches. Work and communicate efficiently in a highly interdisciplinary
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promote equal opportunities to learn, acquire knowledge, participate, and make a difference. As an equal-opportunity employer, Aalto University bases its recruitment decisions on applicants’ competencies
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artificial intelligence/geospatial AI, methods of machine learning and deep learning development of computer vision applications and image recognition methods analysis and production of big data, including
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, automation, information systems, and machine intelligence represent technological methods that are important for future in order to develop environmentally sustainable farming processes, improve energy and
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to promoting diversity, equality, and non-discrimination in all its activities. Thus, we promote equal opportunities to learn, acquire knowledge, participate, and make a difference. As an equal-opportunity