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develop algorithms to identify and predict SRL subprocesses from multimodal learning data (e.g., EEG/fNIRS, eye-tracking, and think-aloud protocols); • Analyze large-scale learning analytics data
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to develop methodologies for real-time modeling and inversion of geophysical well logs, with a particular focus on borehole electromagnetic data during drilling. This includes the further development
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. This role represents a unique opportunity to generate biological insights from our large-scale research datasets including single-cell multiomic sequencing data from skin and blood to enable
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turbulence data, together with fine-scale profiles from standard Argo floats, to quantify rates of vertical and horizontal ocean mixing, and you will apply inverse methods to investigate the role
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large, comprehensive, research university and for nearly two decades, has transformed into the “New American University ,” one dedicated to the simultaneous pursuit of excellence, broad access to quality
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the presence of significant confounding factors Organise large-scale sequence data sets Communicate results at project meetings and conferences Present research outputs, including drafting academic publications
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appointee will join the LEO Dr. David P. Chan Institute of Data Science and will be expected to: (i) carry out research and submit papers to top journals in the field of large vision models or large language
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large databases is required. The candidate is expected to partake in design of the epidemiological studies, statistical work (SPSS but also other programs such as R), presentations and preparation
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electromagnetic data during drilling. This includes the further development and application of fast solvers for Maxwell’s equations and nonlinear inversion algorithms that we have already developed in a previous
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responsible for maintaining high quality research procedures and will work as part of the team and liaise with three recruiting sites in setting up the study, monitoring participant recruitment, data collection