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National Aeronautics and Space Administration (NASA) | Pasadena, California | United States | about 5 hours ago
experience programming in the Unix/Linux environment using Python, Java, C/C++, or Julia; must have experience with algorithms, numerical techniques, and computational methods, specifically for uncertainty
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topological optimization of light guidance in HCFs, and numerical simulation of thermo- and fluid dynamics under fiber-drawing processes. Apart from the main tasks above, the postdoc can be involved in
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possible sounding capabilities with current laser-produced sources, and (2) implementing experiments to test the predictions of these calculations and optimize the sources. The missions follow these lines
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uncertainty quantification into scientific machine learning workflows and optimize the design of computational (ABM) and wet-lab experiments. • Collaborate with mathematical modelers and experimentalists in
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. This will be made on different Cu-FR4-Cu laminate test-structures with a FR4 thickness ranging between 35 to 100 μm. A preliminary assembly process optimization will be performed (e.g., temperature
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to numerous preclinical research projects focused on the development of novel molecular magnetic resonance imaging (MRI)-based techniques for early detection, disease phenotyping and monitoring treatment
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algorithms to enhance the design optimization process Create predictive models using Python-based frameworks (e.g. scikit-learn, PyMC) to accelerate design iterations Integrate ML approaches with finite
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strategies (e.g. predictive or machine learning approaches) to improve performance and reduce costs. Collaborating with industrial partners on design optimization, life-cycle analysis, and business case
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on design optimization, life-cycle analysis, and business case development. Publishing results in journals and conferences, and engaging with stakeholders through workshops and demonstrations. The position is
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testing, and advanced process simulation, with the objective of optimizing grinding performance and enhancing resource recovery. The ideal candidate will have a strong background in mineral processing