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, facilitating impactful multidisciplinary collaboration, scholarly advancement, and the creation of tools and public goods. Requirements Applicants must have (or expect to have at time of appointment) a PhD in
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developing foundational statistical/AI/data-driven techniques for uncertainty quantification and visualization of complex, large-scale 2D/3D scientific data. Publishing research in leading peer-reviewed
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: Experience with analyzing GPS tracks Good data-handling skills and ability to use R (compulsary) and preferably also Python and/or GIS competently Statistical/causal inference knowledge PhD degree in a related
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of Human-Centered AI Technologies, leveraging advanced Generative AI and novel interaction technologies. PostDoc and PhD Positions in Human-Centered AI Potential Project Ideas are: AI in Education AI Safety
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Postdoctoral Associate Required Qualifications: (as evidenced by an attached resume) ● PhD (or foreign equivalent) in hand by May 2026. ● Strong background in neuroscience. ● Solid
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contact Hong Zhu, Professor, at hzhu2m@virginia.edu. Minimum Requirements: Doctoral degree Preferred Qualifications: PhD in biostatistics, statistics, or a related quantitative field by the appointment
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academia, participate in the University’s Individual Development Plan policy for postdoctoral scholars, have a PhD or equivalent terminal degree (such as MD, DVM, PsyD, PharmD, etc.), and candidates should
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that incorporates a broad range of neutrino and dark-matter models, assessing their effects on large-scale-structure (LSS) statistics as measured by the power spectrum and bispectrum of galaxies or intensity maps
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applicants who combine strong quantitative skills with a deep interest in the fundamental mechanisms shaping plant communities and their response to climate change. Qualifications: • PhD in Ecology or a
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support to the PI across project needs as they evolve over the course of the grant. Required Education and Experience PhD in environmental epidemiology, environmental health, exposure assessment, health