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close collaboration with other postdocs and doctoral researchers of our team. The group currently consists of five postdocs, four doctoral researchers, and several undergraduate researchers. We work
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has been appointed). There might be a possibility for an extension of the contract depending on the project. The position is opened at the Department of Agricultural Sciences, Faculty of Agriculture and
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evaluating them on real-world data (e.g., in iCAN ) in collaboration with precision cancer medicine experts. We strive to revolutionize cancer care through the power of massive data and machine learning! Key
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will focus on developing dimension reduction methods for multivariate spatial data which might be also of functional nature, especially in a blind source separation framework. Five percent of the working
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dimension reduction methods for multivariate spatial data which might be also of functional nature, especially in a blind source separation framework. Five percent of the working time will be allocated
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considered advantageous. A problem-solving mindset, excellent written and oral skills in English, and the ability to work productively both independently and as part of a team are a necessity. A willingness to
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or similar approach Has a strong background in climate change adaptation research Has high motivation for academic research Has the ability to conduct independent scholarly work and willingness for an extended
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should have a strong interest and motivation for applying algorithmic discoveries in biology and possess the ability to carry out independent research. Salary and benefits The starting salary
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confirmed defence date) in Political Science, Law, Economics, or a related discipline Demonstrated academic writing skills and analytical ability Familiarity with digital policy areas (e.g. data governance
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PhD degree in experimental particle physics Good skills in written and spoken English Interest in performing research on topics close to the project scope Researcher's mindset and ability