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Researcher (R1) Application Deadline 30 Oct 2026 - 22:59 (UTC) 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
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Institute of Neuroscience and physiology, Sahlgrenska Academy, university of Gothenburg | Sweden | 3 days ago
Stage Researcher (R1) Application Deadline 16 Oct 2026 - 12:00 (UTC) Country Sweden Type of Contract Temporary Job Status Full-time Is the job funded through the EU Research Framework Programme? Not
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) 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 Is the Job related to staff position within a
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distributed embedded systems that interact with each other and their environment to enable secure, goal-driven, autonomous and evolvable solutions. Project description E2PACKMAN is a €93.7 million European
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conduct world-class applied research. We change and make a difference. Do you want to become one of us? The Department of Computer Science (DIDA) is one of three departments at the Faculty of Computing
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Institute of Neuroscience and physiology, Sahlgrenska Academy, university of Gothenburg | Sweden | 27 days ago
Researcher (R1) Application Deadline 21 Sep 2026 - 12:00 (UTC) 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
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) 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 Is the Job related to staff position within a
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21 Sep 2026 - 12:00 (UTC) 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 Is the Job related
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for even gender distribution among employees and values diversity. Want to know more? Doctoral education programme: Resource Recovery Research Areas: Resource Recovery Research Group: Resource Management
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in practice when the dimension of the data-generating process exceeds the sample size, this project will contribute by developing the distributional properties of generalized inverses of the high