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energy, energy storage, electronics, medicine, sustainable manufacturing, etc. The main focus for the advertised position is novel machine learning method development. However, you will be part of a larger
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must have a PhD or equivalent Strong background in biomedical science or a related field Practical experience and scientific expertise in biomedical methods such as ELISA and immunohistochemistry, as
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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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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 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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) 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
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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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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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of extremist messages, or the use of social media or AI in politically motivated criminal practices. The dissertation work may be conducted using qualitative, quantitative, or mixed methods, and should connect
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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