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available single-cell sequencing data generated from patient samples and mouse models, we will enhance and apply machine-learning based algorithms to deconvolute bulk tumor RNA-seq samples to distinct immune
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studies by cryo-electron microscopy (cryo-EM) and/or X-ray crystallography. Perform data processing and model building (e.g., Relion , CryoSPARC , Coot, PyMOL ). Option 2 : Cell Biology Design and execute
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in live or fixed organisms, cells or tissues - Experience with data analysis in Python, R or similar - Experience working with animal models AND - Experience with mass spectrometry, including sample
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skills in data analysis, machine learning, as well as in mathematical and computational modelling? You will have the opportunity to investigate innovative solutions using machine learning algorithms and
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electrolyte and water reabsorption. The postdoc will be expected to explore the potential of modulating bile acid signaling in cell and mouse models and perform metabolomic and transcriptomic analyses
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multi-disciplinary approaches to answer these key questions including; immunology, oncology (in vitro model-organoid systems, ex vivo tissue culture), microbiology, next generation sequencing (16S seq
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molecular engineering/alteration and interrogation of prostate cancer cell line models, RNA-seq/ChIP-seq, etc. Compensation (including a generous package of fringe benefits) is dependent upon qualifications
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virological and immune system-based research through long-standing community partnerships and clinical trials research, along with using laboratory models of virus infection. The successful candidate will work
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) analysis Mathematical modelling Microbiology Molecular biology We approach science with the view of physics, aiming to identify principles behind complex systems. We collaborate closely with engineers
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, to support the development of murine infection models for antifungal efficacy testing as well as for use in in vitro screens. Secondly, to contribute to the development, optimisation and implementation