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Archive, U.S. Forest Inventory and Analysis program, sPlotOpen) along with geospatial soil and climate data to apply resource colimitation theory in the refinement of correlative-based species distribution
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, Engineering, Geospatial Science or a closely related field is required. PH.D. is preferred. The successful candidate must have significant coursework and/or expertise in land surveying. Preference will also be
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, including time series analysis and statistics (e.g. mixed effects modelling) Capacity to develop computer code and experience with programming languages (Matlab, Python, R) and geospatial tools (e.g. ArcGIS
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Geospatial analysis, machine learning, and predictive modelling, Have a good command of programming tools such as R packages, Phyton, and other programming languages Publications in the field Excellent
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requirements for doctoral studies in each subject are specified in the relevant general syllabus, available at https://www.lusem.lu.se/research/doctoral-studies. Other requirements A proficient level of English
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for someone with graduate or postgraduate level competence in one or more relevant subject areas, including computational simulation, model testing, and geospatial analysis. The term of this appointment is 1
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decision support Analysis of large-scale geospatial, sensor, and remote sensing datasets (e.g., multispectral, hyperspectral, LiDAR) Predictive modeling for crop performance, resource efficiency, and climate
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from the new FireSat constellation) and geospatial analysis. Topic 2 requires a combination of field and remote sensing approaches. For topic 3, experience with processing large geospatial datasets is
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: This is a 12-month, full-time position with benefits. Visas may be arranged. You can find more information on benefits for Harvard employees here: https://hr.harvard.edu/health-welfare-benefits. Basic
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, and proven experience with geospatial data. Salary Range: €43,000 - €55,000 Per Annum Appointment on the above range will be dependent upon qualifications and experience. Closing date: 12:00 noon (local