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uniquely conserved—TRIM in animals and polyD/E in eukaryotes—setting them apart from classical PQC mechanisms. We are exploring their molecular mechanisms, their roles in aging and neurodegenerative diseases
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2025. We seek to recruit a Research Associate specialising in statistical modelling and machine learning to join our multi-university multi-disciplinary team developing a groundbreaking technique based
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(including Crohn’s disease and ulcerative colitis) using molecular and cell biology, multi-omics technologies, murine models, and human tissues. We currently have three major focuses: 1) Innate lymphoid cells
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on the development of anti-infective drugs and vaccines using the pig as a model platform. Main tasks will include the design, coordination, and execution of pig experiments, and assessment of drug and vaccine
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advance regenerative medicine. For more information about the lab, please visit https://mesa-lab.org/. Projects will utilize in vivo mouse models, transcriptomic techniques, and advanced intravital imaging
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models with a group of highly motivated scientists to employ interdisciplinary approaches such as retinal cell biology, functional genomics, imaging, and biochemistry. The Chen Lab has a well-recognized
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-lab-taosheng.html ) studies: (1) the chemical regulation of nuclear xenobiotic receptors, (2) the molecular basis of signal crosstalk among nuclear receptors, and (3) the mechanism of selective
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harnessed for further engineering. The ideal candidate has led a molecular-level scientific research project and has technical expertise in CRISPR, gene transformation, or other genetic tools applied to one
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analyzing whole organism models (zebrafish and mouse) to dissect the pathophysiology of a recently identified rare pediatric neurometabolic disorder. The approach involves mainly deep longitudinal phenotyping
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to numerous preclinical research projects focused on the development of novel molecular magnetic resonance imaging (MRI)-based techniques for early detection, disease phenotyping and monitoring treatment