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, computer vision and pattern recognition, atmospheric modelling, and computational spectroscopy. We focus on in-depth understanding of data and related algorithms, data analysis, and machine learning. Our
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-depth understanding of data and related algorithms, data analysis, and machine learning. Our cross-cutting theme is machine learning-enhanced computational engineering. You’ll have an excellent
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environment, and continued commitment to your support, learning, training, and development. For further information, please contact Professor Ville Uusitalo, +358 40 586 4486, ville.uusitalo@lut.fi, and
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to your support, learning, training, and development. For further information, please contact Timo Kärri, Professor, +358 50 322 3320, timo.karri@lut.fi. Please submit your application by December 1, 2025
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environment, and continued commitment to your support, learning, training, and development. For further information, please contact Lea Hannola, Associate Professor, +358 40 822 3982, lea.hannola@lut.fi
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leadership principles and operational excellence. The purpose of the professorship at Ekhva is to advance continuous improvement, process development, and quality enhancement in order to build a learning