291 evolution "https:" "https:" "https:" "https:" "https:" "https:" "University of Texas at Austin" research jobs in Sweden
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. The application should be registered via Umeå University’s e-recruitment system Varbi (https://umustipendie.varbi.com/en/what:job/jobID:887298/ ) and submitted by the deadline 18 March 2026. Please apply at with
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representatives: https://internt.slu.se/en/my-employment/employee-associations/kontaktpersoner-vid-rekrytering/ The Swedish University of Agricultural Sciences (SLU) has a key role in the development
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research within Unmanned Traffic Management (UTM). In this role, your primary responsibility will be the hands-on development of advanced simulations and prototypes that help us test and validate new UTM
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inclusive work environment with excellent opportunities for professional development. About the position Type of employment: Fixed-term employment according to the postdoctoral agreement. Scope: 100% (80
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such as the heart and nervous system, invariably with fatal consequences. The project will focus on probing the molecular factors underlying this instability (see for example https://www.nature.com/articles
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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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distributed WaRM experiment (for details see here: https://onlinelibrary.wiley.com/doi/10.1002/ece3.9396). The employment is fulltime for three years. The deadline for applications is March 26, 2026 and the
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on the long term globally distributed WaRM experiment (for details see here: https://onlinelibrary.wiley.com/doi/10.1002/ece3.9396 ). The employment is fulltime for three years. The deadline
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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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, etc.) development of predictive models and digital decision-support tools for nutrition and health method development in causal inference, integration of heterogeneous data sources, uncertainty