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the level of individual cells. Yet much of the biological information embedded in these data remains unexplored. The next step is to convert these time-lapse images into accurate single-cell trajectories and
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. The Fellow will work in close partnership with the lab's experimental team to build and apply analytical frameworks that translate these data into mechanistic insight and therapeutic hypotheses. As part of
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genetic, neuroimaging and clinical data, will be combined to generate novel insights into biological and developmental processes contributing to autism and related traits. You will be responsible
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New Zealand, in the continuation of their studies in New Zealand or the Commonwealth. For more information visit Universities NZ . Value $5,000 Closing Date 1 March Selection Criteria Applicants must be
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on effective and safe inspection and maintenance. Current maintenance approaches rely primarily on turbine sensor data, meaning that human and organizational factors are largely overlooked. This represents a
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the mechanisms contributing to sporadic ALS progression, helping to pave the way for novel therapeutic strategies. They will collaborate closely with data scientists and experimental colleagues to ensure thorough
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work as part of a larger team to assist with collecting and analyzing data gathered from human subjects, both in field, clinic and lab studies as part of evaluations of the technology. A large part of
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. Analyze experimental data and interpret results to write reports and summaries of findings, including grant preparation and presentations, and look for opportunities to co-author publications. May be
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, modulation instability, and supercontinuum generation. Integrate experimental data with AI models, using machine learning to uncover hidden physics, accelerate simulations, and discover new operational regimes