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experience in agronomy, soil science, engineering methods, and precision agriculture in semi- and hyper-arid regions. Specifically, we will be testing the effects of soil amendment technologies pioneered by
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: The candidate should have expertise in machine learning and computational methods applied to seismic imaging, inversion, earthquake monitoring, or subsurface characterization. The candidate should have expertise
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filled. High priority will be given to the overall originality and promise of the candidate’s work rather than the candidate’s sub-area of specialisation. An earned PhD in Statistics or a related field
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technologies. Key Responsibilities: Develop and optimize hard carbon synthesis processes using bio-based and non-bio-based precursors. Explore innovative methods to enhance material properties for energy storage
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-based precursors. · Explore innovative methods to enhance material properties for energy storage applications and other emerging technologies. · Conduct detailed structural, chemical, and
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covering continual learning methods relating to theme (b) is available here: More information about the research group can be found here: Requirements include good communication (verbal, writing, etc) and
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using a combination of multimodal imaging, computer vision, and lab automation platforms that govern entire workflows (e.g. ThermoFisher momentum software scheduling Hamilton liquid handlers and high-end
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holding a PhD in chemical, environmental or process engineering, to apply for a full-time post-doctoral fellowship position in the field of water desalination, focusing on the development of an artificial
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is to develop a modeling framework including the use of Random-Walk method to predict NMR measurements, pore-scale finite-element modeling on 3D digital models, generated from CT-images to predict
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experience with molecular and cell biological methods. The applicant will work to advance our knowledge of viral vector production in versatility, stability and efficacy with modern techniques from plasmids