914 machine-learning "https:" "https:" "https:" "https:" "U.S" "U.S" positions in Sweden
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Field
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communications theory methods Applying optimization techniques and machine learning/AI approaches Conducting simulations and experimental validations Collaborating with Ericsson and Chalmers researchers Publishing
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: October 2026 Full call details, eligibility criteria, application templates, and a matchmaking platform for identifying potential supervisors are available at: https://www.scilifelab.se/data-driven/ddls
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methods, including GIS and spatial analysis. Applicants are invited to visit our departmental website to review the kinds of research we do in the department (https://www.uu.se/en/department/human-geography
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offering a high living standards, access to a sprawling city life as well as the beautiful nature surrounding the city. https://ki.se/en/research/research-areas-centres-and-networks/research-groups/robert
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percent of working hours Contract terms The Doctoral student positions is fully funded from start. The position is a fixed-term appointment of four years, with the possibility to teach up to 20%, which
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networks Scientific programming for simulation, data analysis, and reproducible workflows (e.g., Python/Julia/Matlab/C++) Machine-learning–inspired methods for reservoir/neuromorphic computing and
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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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regular project meetings and collaborate closely with other members of the research group. Publish scientific articles, both independently and in collaboration with others. Teach up to 20% of your working
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education and societal relations, educational systems, school development and leadership, adult education, inclusion, learning, language and assessment, and grading issues. A significant part of the
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Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description Project description Third-cycle subject: Technology and learning Teacher