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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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collegial work environment, and continued commitment to your support, learning, training, and development. For further information about the position, please contact Samuli Honkapuro, professor, either by
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recognised as having a significant influence on their field. For more information on the tenure track model and the assessment criteria, please see https://www.helsinki.fi/en/about-us/careers/academic-careers
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be exempted from the Swedish requirement. The employer will support the appointee’s language learning. Read more about the language requirements: https://www.helsinki.fi/en/faculty-educational-sciences
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field, and be recognised as having a significant influence on their field. For more information on the tenure track model and the assessment criteria, please see https://www.helsinki.fi/en/about-us
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good proficiency in English. The employer will support the appointee’s language learning. Read more about the language requirements: https://www.helsinki.fi/en/faculty-educational-sciences/faculty/work
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, learning, training, and development. For further information about the position, please contact Professor Marko Torkkeli either by phone (+358 40 7611223) on Thursday 23 April 2026 at 10:00-14:00 (UTC +3
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) and INSTRUCT projects (2025-2029). The researcher may participate also other research projects. Our expectations of the applicant - a doctoral or master’s degree in a relevant field, e.g. statistics
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, particularly cell culture, with careful working style Strong organizational skills and attention to detail Ability to learn quickly and adapt to changing tasks Capability to work both independently and as part
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Swedish language proficiency requirement. More information: Instructions for applicants of teaching and research positions | University of Helsinki and https://www.finlex.fi/fi/laki/alkup/2009/20090770