31 programming-"IMPRS-ML"-"IMPRS-ML" positions at Swedish University of Agricultural Sciences
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. change detection, semantic segmentation, or multimodal fusion, experience in deep learning for image analysis using time series satellite data, excellent programming skills (Python, PyTorch/TensorFlow
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sensing, forestry, ecology, agriculture, and computer sciences. Experiences in scientific programming and 3D remote sensing data processing and analysis are required, as well as fluent in English for
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for Bachelor and Master degree programs, as well as offering Ph.D. education in applied economics, business administration, and economics. The Department is located at two campuses: Uppsala and Umeå. Among many
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leading to production and harvesting in the regulated countries moving to unregulated countries. The position is part of a joint research program between Swedish University of Agricultural Sciences (SLU
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, second and third cycle levels. The department is responsible for ca. 30 courses within SLU's educational programs, e.g. the agronomy programs, the bachelor's program in biology and environmental science
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of forests in climate change are now key social issues that require more knowledge. In order to both sustainably use and safeguard forest biodiversity, a coherent basic science research program is needed
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for early-career researchers in the field of environment and sustainability. The position includes, among other things, participation in a leadership development program and the supervision of a doctoral
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international collaborations. The department is responsible for courses in 14 of SLU's educational programs, e.g. the agronomy programs, the bachelor's program in biology and environmental science, the master's
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and safeguard forest biodiversity, a coherent basic science research program is needed that addresses large and complex issues and develops new analytical tools. That’s why the WIFORCE Research School
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advanced models for genomic selection to improve breeding programs in plant and animal breeding. You will analyze genetic data: Use bioinformatic and genomic methods to process and interpret large-scale