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management Nordic forestry Remote sensing data: ALS, TLS, satellite (e.g. sentinel2), aerial images Statistical modelling and analysis GIS e.g. ArcGis, Qgis, R Programming, e.g. R, Python, C etc. Field work
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Forest ecology and management Nordic forestry Remote sensing data: ALS, TLS, satellite (e.g. sentinel2), aerial images Statistical modelling and analysis GIS e.g. ArcGis, Qgis, R Programming, e.g. R
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two PhD student positions to carry out research with the Signal Processing group in the area of next generation space-terrestrial wireless communications and sensing. We are looking for ambitious and
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positions to carry out research with the Signal Processing group in the area of next generation space-terrestrial wireless communications and sensing. We are looking for ambitious and creative candidates with
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managed boreal forest landscapes. The research will be done in terrestrial ecosystems. It aims to include experimental and observational studies (e.g. using field, lab, remote sensing data) along
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experimental and observational studies (e.g. using field, lab, remote sensing data) along environmental gradients to increase understanding of how different types of forest management (e.g. continuous cover
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of additional areas of interest. Qualifications: The successful candidate must meet the following qualifications: MSc degree in Environmental Sciences, Physical Geography, Ecology, Biology or another related
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, forestry, bioinformatics, or a related field - Strong demonstrated interest in biodiversity, molecular methods, or forest ecology - Advanced Skills in R/Python, GIS, bioinformatics, and molecular lab work
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methods, or forest ecology - Advanced Skills in R/Python, GIS, bioinformatics, and molecular lab work - Ability to work independently and in multidisciplinary teams - Strong English communication skills
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transmission and processing for remote actuation. The proposal targets two interdependent challenges: the inherent complexity of end-to-end information flow spanning sensing, computation, communication, and