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Reactor) designs. This system constitutes a corium containment strategy in the event of a severe accident. Therefore, understanding the thermodynamic properties of the corium is essential for predicting its
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. The successful candidate will contribute to the development of predictive numerical models and experimentally validated designs for intricate mechanical assemblies, deployable structures, compliant mechanisms, and
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at the intersection of mathematics, computation, and cancer biology. We develop mechanistic, predictive models of cellular decision-making to address fundamental and translational challenges in cancer, including drug
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in New York, across the nation, and around the world. Position Function The CNCPS was modified to be able to predict nitrogen (N) and phosphorous (P) excretion, and this was published by Fox et al
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. For the Working Group “Ecosystems in Transition” in RD1 at PIK, we are offering a PhD position (m/f/d) (Position number: 10-2026 PhD ARTECO) in the field of ecological modelling of complex arctic landscapes
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and researchers to gain insight into novel methods used to predict toxicity of various chemicals and gain understanding of how these chemicals impact in vitro, cell-based model systems. Why should I
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background in nonlinear optics, ultrafast photonics, and integrated photonics, alongside the ability to develop predictive models for optical materials and photonic devices. The successful candidate will work
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speech processing, a research question that is rapidly gaining in importance. The project is centred on the hypothesis that the cerebellum conveys predictions about upcoming speech sounds to the neocortex
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research, teaching, and promoting an environment that allows all members of the department to thrive. Principal concentrations include weather prediction, air quality, air-sea interactions, climate modeling
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Postdoctoral Positions for Computational Genomics, Cancer Genetics, and Translational Cancer Biology
their impact on the tumor immune microenvironment and immunotherapy response. 3) Developing clinical-grade mechanism-driven AI models (iGenSig-AI) for predicting responses to targeted therapies and