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help us develop new, innovative methods to extract knowledge from immune cell movement videos. When thinking of cells, most people imagine static building blocks. Yet many processes in health and disease
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in biology? Then you have a part to play as a PhD candidate. By combining simulations and machine learning, you will help us develop new, innovative methods to extract knowledge from immune cell
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; cell culture; RNAseq and analytical methods such as fluorescence spectroscopy; MALDI-TOF; and HPLC. Interest in Organic Chemistry is preferred. You will communicate your findings through publications in
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, but validation studies in large cohorts are lacking. In this project, you will validate the predictive value of plasma SCFAs for cancer immunotherapy response in a large cohort of non-small cell lung
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attitude. You have creative thinking skills and a high degree of independence. You have preferably experience with any of the following: single-cell RNA-sequencing, epigenomics, proteomics, bioinformatics
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to this collaboration on these four themes through our expertise in metabolomics, cell biology and biochemistry, environmental microbiology, biotechnology, microbial physiology and bioinformatics. Radboud University
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microbiology 2. Carbon/methane cycle microbiology 3. Host-microbe interactions 4. Bioremediation We contribute to the collaboration on these four themes through our expertise in metabolomics, cell biology and