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diseases. Specifically, this postdoctoral fellow will focus on establishing biology models and assays relevant to the in vivo cell therapy platform, generating and testing novel in vivo cell therapy designs
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of Oslo. Job description A fully funded PhD position is available on the development of spatiotemporal statistical modelling of climate-sensitive infectious diseases, with a particular emphasis on Bayesian
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Summary A postdoctoral position is available at the Center for Earthquake Research and Information, University of Memphis for at least two years. The postdoc will work in the earthquake physics group
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enhance our contribution to society. Responsibilities* The successful candidate will work on projects performing analysis of PET neuroimage data, including kinetic modeling and multimodal data synthesis
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transcriptomic data, that will be integrated with clinical metadata and whole-genome data for developing machine learning models to identify and predict patient factors driving toxicity response and sensitivity
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, and utilize the state-of-the-art multi-scale atmospheric models, along with measurement and statistical approaches, to understand the mechanisms that drive the climate-air quality interactions, and
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researcher to join our team and advance our understanding of protein adsorption at interfaces, an area critical to biologics development. This research project will focus on developing a predictive model for
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for driving research studies using electrophysiology methods aimed at investigating mechanisms underlying sensitization of nociceptive neurons in the context of migraine chronification. The postdoc will design
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Lawrence Berkeley National Laboratory - Nuclear Science | Berkeley, California | United States | about 12 hours ago
. Characterize radiation detection materials using a variety of methods. Develop mathematical models to support experimental data interpretation and development of the future materials. Function independently and
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on developing and applying foundational AI models to investigate clinically relevant cancer vulnerabilities and their relationship with molecular context. Spanning functional genomics and large-scale clinical