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Field
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simulations of the proposed functionalities, including the waveguide ability to detect the presence of analytes. These sensing capabilities will be explored through both optical absorption mechanisms and phase
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to quantify energy consumption, performance and cost benefits. In this role, a successful candidate will perform vehicle modelling and simulation of advanced powertrains to quantify the impacts of new component
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. In addition, IFAE is deeply involved in the detector R&D and optical simulation activities of ET and CE. IFAE works with CERN in the design of the ET vacuum pipes. The IFAE research program spans many
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standard solar cell manufacturing processes. The project will also include optical simulation tasks and advanced luminescence characterization experiments. The postdoc will also contribute to the design of
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quantum gravimeters. Main responsibilities include: Operating a quantum gravimeter and planning/conducting measurements in the field and laboratory. Processing, analyzing, and reporting gravimetric and
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Sensor Fusion: Strong background in processing and fusing data from cameras, LiDAR, radar, or other sensors for robust autonomous system perception ML Engineering and Experimentation: Proficiency with
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. Process simulation, cost, life cycle, and social assessment of CCUS value chains. Reactor design, optimization, and sizing using phenomenological and/or CFD methods. Energy system analysis. Strong
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by Dr. Tim Pleskac (cognitive and decision modeling) and Dr. David Crandall (computer vision and AI). The postdoc will lead the development, integration, and testing of computational models of decision
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Postdoctoral Appointee - Uncertainty Quantification and Modeling of Large-Scale Dynamics in Networks
mathematics, or a related field Candidates should have expertise in two or more of the following areas: Uncertainty quantification, numerical solutions of differential equations, and stochastic processes
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radiation and using Monte Carlo simulation software (MCNP, GEANT4). Knowledge of multi-element analytical techniques (PIXE, XRF, ICP-MS). Valorization of Industrial Waste: Experience in developing processes