884 machine-learning "https:" "https:" "https:" "https:" "https:" "U.S" "U.S" positions in Sweden
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generative machine learning models to create an active learning cycle to identify materials with adequate properties. Promising materials will be synthesized, characterized and evaluated in lab. This will help
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and CH4) from headwaters, and use of machine learning and process-based model for large scale assessments and projections of the land-water carbon cycle to variation in climate conditions. The detailed
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Umeå Plant Science Centre (UPSC, https://www.upsc.se ) which is a centre of excellence for experimental plant research and forest biotechnology in Northern Sweden. Our mission is to perform excellent and
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machine data analytics to new harvesting system designs. The Department of forest genetics and plant physiology is part of Umeå Plant Science Centre (UPSC, https://www.upsc.se ), a world leading centre for
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computational methodologies, ranging from atomistic and electronic-structure–based materials modeling and characterization, via machine-learning and high-throughput methods, to ab initio calculation
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international academic institutions and 14 industry partners (https://euraxess.ec.europa.eu/jobs/401249 ). We work together in the field of fluid-structure interaction in technical systems and industrial
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terms The Doctoral student positions are fully funded from start. The position is a fixed-term appointment of four years, with the possibility to teach up to 20%, which extends the position up to five
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doctoral degree. More about being a doctoral student at LTH on lth.se. https://www.lth.se/english/study-at-lth/phd-studies/ Subject and project description ELLIIT (https://elliit.se ) is a strategic research
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well as online data collection (experiments, surveys). Expertise in advanced machine learning techniques and large language models (LLMs) —including web scraping, text mining, and neural networks—is considered a
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teaching and learning. The work duties include: The post-doctoral fellow will investigate how stellar and geomagnetic information is sensed and processed by the Australian Bogong moth Agrotis infusa, a model