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to sponsored research projects with industry partners; develop innovative analytical and computational methods; publish findings in leading academic journals; mentor graduate students; support graduate-level
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biophysical approaches at the cellular, protein, and whole-animal levels to identify the molecular mechanisms underlying heart and skeletal muscle diseases. Current studies utilize methods ranging from protein
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, bioassay development, bioanalytical methods operation. Candidates should demonstrate strong communication skills, a record of independent research productivity, and enthusiasm for working both independently
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to the discovery of dozens of classes of bacterial riboswitches and other structured noncoding RNAs. We are now applying similar genome-scale discovery methods to identify functional RNA regulatory elements in
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candidate will have an existing research profile that uses ethnographic methods to explore questions relevant to the social and ecological effects of livestock and agricultural infrastructures on landscapes
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such as Bayesian modelling and optimal control theory. Using state-of-the-art methods – including virtual reality, wearable sensing, motion platforms and advanced data analytics – you will place particular
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molecular biology techniques. In vivo testing using animal models Perform experiments to evaluate the biodistribution and efficacy/safety of nanoparticle formulations. Interpret data with advanced methods
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the engaged research process, working with local communities to establish, refine and finalise energy narratives (notably by incorporating resident-led and other engaged research methods), and producing project
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biostatistics faculty collaborating with the Childhood Cancer Survivorship Program (CCSP). You will develop innovative biostatistical methods for childhood cancer survivorship research and collaborate with CCSP
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or quantitative methods. We are open to a range of methodological backgrounds, including digital trace data analysis, natural language processing, machine learning, experimental design, causal inference, and