188 engineering-computation-"https:" "https:" "https:" "https:" "https:" "https:" "UCL" "UCL" "UCL" PhD positions in Sweden
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:59 (Europe/Stockholm) Country Sweden Type of Contract Temporary Job Status Full-time Is the job funded through the EU Research Framework Programme? Not funded by a EU programme Reference Number PA2026
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of Technology , we conduct advanced research in data-driven nutrition, health, and food science. With large-scale diet and health data, omics data, biomarkers, digital food and health services, we establish
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Högskoleförordningen 5 Chapter 1-7 §§ and in the University rules http://regler.uu.se/ . The rules of the doctoral program are found in the General Curriculum of the Doctoral Program in Human Geography (Allmän
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social issues that require more knowledge. In order to both sustainably use and safeguard forest biodiversity, a coherent basic science research program is needed that addresses large and complex issues
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the Faculty Board of Science and Technology, and be deemed to have the overall ability required to benefit from the education (Higher Education Ordinance, Chapter 7, Section 35). General entry requirements
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the role 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
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educational programs in Computing Science, we are now seeking a PhD student with focus on Software Lifecycle Security. The Department of Computing Science has been growing rapidly in recent years, with a focus
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Luleå University of Technology experiences rapid growth with world-leading expertise within several research areas. Our scientific and artistic research and education are conducted in close
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its general study plan, is available at: https://www.umu.se/en/department-of-political-science/education/doctoral-studies/ The students will work in Umeå, and the doctoral program is given on site
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, and datasets; often at substantial computational and environmental costs. This PhD project targets sustainable and resource-efficient machine learning with a focus on methods that reduce compute, energy