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, which causes reduced performance and accelerated material degradation in seawater. This project will experimentally investigate cavitation erosion in composite materials and develop a structural health
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processing, while maintaining high efficiency and selectivity in flotation performance. Responsibilities: Develop and synthesize bio-based flotation additives (e.g., collectors, dispersants, depressants
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interested in computational materials design and discovery. The successful candidate will develop new, openly accessible datasets and machine learning models for modeling redox-active solid-state materials
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Google Earth Engin, R, Python, and STAN (e.g., deep learning, Bayesian regression models, spatial analyses), and running analyses on a high-performance computing cluster. Demonstrated record of publishing
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with basic continuum and rock mechanics, including computational approaches. * Programming in C / python / Julia or equivalent, and ideally some experience with high-performance computing * Familiarity
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-postdoc Early Career Professional Development: Career and professional development are important components of your postdoctoral training. FES’s goal is to help postdoctoral fellows perform and publish high
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Planetary Health (HPH) (link is external) and Project Unleaded (link is external) for an exciting postdoctoral fellowship that contributes to a high-impact global program with a mission to create a
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(energy auditing, GHG accounting, resource recovery)*Strong publication record and excellent written/verbal communication skills*Experience in coding for high performance computing (e.g., university cluster
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Desenvolvimento Regional (FEDER) through the Regional Programme (CENTRO 2030) of Portugal 2030; reference of operation 21384, operation code CENTRO2030-FEDER-02236100on Balcão dos Fundos. VI.IV - Information and
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of high-dimensional datasets, and developing bioinformatic pipelines for high-throughput analysis in high-performance computing (HPC) clusters. The work provides the possibility to develop skills in