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the sustainable companies and societies of the future. Machine Learning Research Laboratory is looking for a doctoral student in the field of machine learning. We offer state-of-the-art resources
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studies in relation to a specific research aim. At large, PhD studies include a number of doctoral courses, reviewing literature, conducting research studies, and interacting with industrial companies. As a
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provides an international, creative and stimulating research environment. The Department MC2 houses a state-of-the-art cleanroom facility for micro- and nanofabrication, which is used by us for device
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student in the field of machine learning. We offer state-of-the-art resources for performing research and a good academic network in Sweden and abroad. Subject description Machine learning focuses
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and abiotic drivers for the changes in plant root traits and how these changes have impacts on ecosystem carbon and nitrogen cycles. Based on the compiled database of plant root traits and literature
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be working with state-of-the-art dynamic resource allocation techniques as well as Trusted Execution Environments (TEEs). As a doctoral student, you devote most of your time to doctoral studies and the
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of data-driven state-of-the-art image analysis techniques, including novel segmentation and image registration methods, applied on a combination of large-scale private and public datasets. Welcome
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on the compiled database of plant root traits and literature, the PhD candidate will conduct a meta-analysis about the relationships of root traits and biotic and abiotic drivers. Based on a long-term sampling of
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landscape and interactions within lichen thalli will be studied with state-of-the-art advanced microscopy methods. Duties The PhD student will be expected to conduct molecular laboratory work and to prepare
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responses to acute infections and cancer. Using a combination of several state-of-the-art single-cell technologies we strive to understand mechanisms underlying the generation, maintenance and consequences