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://doi.org/10.1126/sciadv.abh1275 ; highlighted by @NCIgenomics as the #1 favorite paper of the year), Analytical Chemistry (https://doi.org/10.1021/acs.analchem.4c05138 ), and Cancer Letters (https
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, such as learning analytics (from e.g. click-stream data, eye tracking, screen capture etc.), surveys, or other large-scale data analysis. However, we also welcome qualitative or mixed-method approaches
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University of New Hampshire – Main Campus | New Boston, New Hampshire | United States | 31 minutes ago
contexts. Design and execute evaluation studies (analytical and/or user-centered) to assess interpretability, robustness, and usability of proposed symbology. Contribute to related research in nautical
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encourage research that combines socio-technical perspectives with quantitative methods, such as learning analytics (from e.g. click-stream data, eye tracking, screen capture etc.), surveys, or other large
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• Significant experience in data analytics, statistics and/or urban analytics • Experience in urban environmental sustainability, urban environmental policy and environmental education is advantageous but not
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external partners, you will contribute to the production of high-quality analytical outputs and publish results in leading journals. The postholder will have substantial ownership over one or more core
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engage in clinical research in a supportive learning environment. Diverse mentorship references for the PI are available upon request. The ideal candidate will have a PhD in psychology, neuroscience, or a
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researcher with a doctoral degree and a strong background in clinical or translational research. The successful candidate will demonstrate scientific curiosity, strong analytical and communication skills, and
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AFSD, cold spray, and LPBF Strong background in materials science, including characterization techniques such as SEM, TEM, FIB, XRD, nano-indentation, etc. Experience with analytical/numerical thermal
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We have an exciting opportunity for a Research Assistant/Associate to make a contribution to an ERC-funded project "Dynamic network reconstruction of human perceptual and reward learning via