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Field
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(e.g. Python, R) Experience in the use of neuroimaging analysis (fMRI, MRI) to study mechanisms of brain function Previous experience of using Bayesian methods in both model development and fitting
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. We take a bottom-up approach to robotics and develop soft materials and devices that would enable unusual form and unconventional functions for broader robotic applications. Job description Track 1
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of using Bayesian methods in both model development and fitting. Previous experience and knowledge of research methods and study design in clinical trials. Knowledge of Good Clinical Practice (GCP) in
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work and how they might be misused or abused (both intentionally and unintentionally) Boundary objects that can be used to bridge the divide between educators and AI experts (e.g. causal DAGs, hybrid
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statistical analysis and modeling techniques such as Gaussian process modeling, data assimilation, and Bayesian analysis; and 4. Open-source scientific software development. Expertise in computational
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) or other expertise relevant to the project objectives (see above) Early career track record including publications or other outputs in the related field In case your background is in psychology or medicine
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for a Postdoctoral Scholar. The Scholar will conduct research on Bayesian spatiotemporal modeling methodology under the direction of Professor David Dunson at Duke on developing novel models motivated by
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unintentionally) Boundary objects that can be used to bridge the divide between educators and AI experts (e.g. causal DAGs, hybrid forums, games) so helping people to understand AI without undergoing formal
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responsibility, particularly in relation to planning, funding, collaborating and publishing research, and mentoring colleagues. 15 Establish and sustain a track record of independent and joint published research
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quantum engineering. The ideal candidate will have a solid track record of experimental research, preferably in low-temperature condensed matter physics, quantum physics, quantum engineering, or related