13 design "https:" "https:" "https:" "Lawrence Berkeley National Laboratory Physics" Fellowship research jobs in Sweden
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been awarded when the appointment decision is made. The ability to plan and carry out research of high quality, teaching skills. Profound knowledge of numerical methods for partial differential equations
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to co-design visions and pathways to aspirational ocean futures drawing on diverse and potentially conflicting knowledge, worldview, and value systems. We will lead the workshop process in each
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Chemical Biological Centre (https://www.umu.se/en/kbc ) at Umeå University and is affiliated with the national Centre of Excellence – Umeå Centre for Microbial Research (UCMR) (https://www.umu.se/en/ucmr
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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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for applicants are available at: How to apply for a position . Where to apply Website https://su.varbi.com/en/what:job/jobID:907631/type:job/where:39/apply:1 Requirements Research FieldPhysicsEducation LevelPhD
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, with emphasis on robustness, generalization, and performance in high-dimensional and noisy biological datasets. See this publication for additional details: https://doi.org/10.1111/ede.12449 . The second
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information For further information about this project, please contact Anders Esberg at anders.esberg@umu.se . We look forward to receiving your application! Where to apply Website https
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look forward to receiving your application! Where to apply Website https://umustipendie.varbi.com/en/what:job/jobID:894758/type:job/where:39/apply… Requirements Research FieldBiological sciencesEducation
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Varbi (https://umustipendie.varbi.com/en/what:job/jobID:894778/ ). The deadline for submitting an application is 1st of March, 2026. Further information For further information about this project, please
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advanced light microscopy data. The lab’s research scope ranges from reinforcement learning for drug design, interpretable ML pipelines for cancer research and diagnosis as well as graph neural networks