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We are seeking a research assistant with a background in computing to develop AI models for image reconstruction from data from our ultra-thin fibre-based spatial frequency domain imaging device
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or computational modeling; prior research funding experience. Additional Information: The initial salary is competitive, based on qualifications and experience, and comes with excellent fringe benefits. Hiring
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the analysis of gene expression and neuronal activity across different models, with the ultimate goal of contributing to the development of treatments that could modify the neurodegenerative progression
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, physical modelling experiments, field investigations, and/or numerical modelling. The specific focus area for the research can utilize any of these tools, or their combinations, and will depend
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will contribute to projects focused on developing advanced machine learning models to quantify phenotypic traits of crops, including corn, soybean, and other selected species. These models will leverage
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derived from paramagnetic ions, as well as the modelling of molecular diffusion processes through membranes, by means of molecular dynamics studies. Different parameters that will affect the relaxivity
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analysis, AI algorithm modeling, testing, and integration into functional systems within the project scope. Specifically, in activities related to behavior modeling from IoT device data, generative AI
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from the TexNet earth observation program or assets that provide quality data. Compare different methods and tools for deformation modelling. Engage in outside funding activities and promote programs
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, understand, characterise, and model the effect of surface roughness on wall turbulence when out of equilibrium. Particular emphasis will be made on determining if any form of flow similarity exists across
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. With cutting-edge research, top-tier education, and extensive collaborations, we are a key force in the field. Our core competencies include in vitro ADME models, advanced in vivo methods, computational