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time will be allocated to teaching or supervision duties. Requirements The successful applicant should have a doctoral degree in statistics, mathematics, machine learning, or other relevant field, and
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dimension reduction methods for multivariate spatial data which might be also of functional nature, especially in a blind source separation framework. Five percent of the working time will be allocated
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located at the Department of Forest Sciences. The university lecturer strengthens the global research and teaching related to the management and sustainable use of forest resources at the Department
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agriculture. Experience in interdisciplinary research that offers innovative, decision-supporting solutions for the sustainable use of natural resources and the enhancement of biodiversity in built environments
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of planetary resources. You will work in a cutting-edge, interdisciplinary research environment in a diverse academic setting, fostering collaborations across multiple disciplines and benefit from LUT's
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use Finland-wide remote sensing resources from one of the consortium members, Finnish Geospatial Research Institute to monitor tree growth in Finland and combine this information with whole genome
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in promoting the energy transition and the regenerative use of natural resources and helps build resilient communities, industry, and businesses through data, research, and education. LUT's campuses
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coordinates multiple large-scale research projects and globally unique data resources, such as FinnGen, nationwide health registry data and the Finnish Twin Study and leads the molecular profiling of cancer
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of natural resources and helps build resilient communities, industry, and businesses through data, research, and education. LUT's campuses are in Lappeenranta and Lahti, Finland, but its impact is global
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disposal strategies and sustainable resource management practices. The project also has synergy the ongoing EURATOM EURAD2 RAMPEC work package, and it is expected that some of the methods developed in HiFi