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to lanthanide molecular magnets. While the SFX2C-1e model has been recently used to model core-level spectra, its combination with EOM-CC for molecular magnets has lagged behind. We will link EOM-CC to SFX2C-1e
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. For the purposes, we develop and use advanced (X-ray-based) methods. Your Job Lead the conceptual design, simulation, and implementation of a unique high-energy X-ray beamline for long-term operando investigations
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National Energy Technology Laboratory (NETL) | Morgantown, West Virginia | United States | about 1 month ago
you for multiple applications in Zintellect, they must click the unique link in each email request, but will be given the opportunity to copy over what they had previously submitted. All documents must
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could develop the algorithms, models and software that: design and simulate self-assembling DNA nanostructures and molecular machines; turn artificial molecular networks into images — reconstructing where
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Science (CECS) - School of Modeling, Simulation and Training Work Schedule Monday through Friday 8:00 am to 5:00 pm Type of Appointment Fixed Term (Fixed Term) Expected Salary $58,000.00 The University of Central
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, all of whom will be supervised by a highly experienced team of four (top) researchers in this field supported by a technician. PhD1 focuses on hybrid traffic flow modelling such as Physics inspired
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to represent and model expectations using formal methods, develop techniques that help a system reason about human expectations at runtime, and evaluate the contributions using simulations and experiments with
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specific research questions: What salient elements in cognitive models represent family forest owners’ perceptions and judgement strategies about forest biodiversity on their ownerships? Do family forest
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The main objective of the project is to develop novel, interpretable predictive models for response to immunotherapy in patients with advanced melanoma, based on the functional activity of gut fungi
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focuses on hybrid traffic flow modelling such as Physics inspired Neural Nets (PiNNs) or “ML inspired” traffic models. PhD2 focuses on data assimilation and estimating start and boundary conditions such as