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information about the program can be found at Doctoral studies at the Faculty of Medicine . Background and description of tasks The PhD student will use state-of the-art methods such as cryo-electron tomography
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logical coherence in the formulation of the aim and the research questions stringency of legal reasoning and analysis adequate selection of methods and theory capacity for creativity and innovation in
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- and wet-lab methods. We combine cutting-edge basic science with strong ties to the clinic and aim to directly influence future clinical practice. The doctoral student project and the duties
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experience working with deep learning methods for biomedical applications. Academic and Project Excellence: Evidence of high-quality research work, as demonstrated by academic grades, the merit of prior degree
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of the student is of a person fully committed to forest economics research with foundational training in research methods. The candidate will be responsible for: integrating economics and natural resource
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ocean, and an urgent need to inform regulatory bodies about associated environmental risks. The work builds upon methods developed in our previous inter- and transdisciplinary work on shipwreck risk
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information about us, please visit: the Department of Biochemistry and Biophysics . About the DDLS PhD student program Data-driven life science (DDLS) uses data, computational methods and artificial
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theoretical research, algorithm design, and the development of software tools that demonstrate the applicability of the new methods. Research environment The positions are hosted by the Department
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cytometry, FACS, and qPCR for quantifying infection; as well as statistical analysis. You are also likely to use CRISPR/Cas9 technology, CLIP assay, co-immunoprecipitation, and other biochemical methods
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) analysing the effects of different trade-offs between timber production and biodiversity under the influence of climate change, and 3) developing optimisation models based on heuristic and AI-based methods