109 algorithm-development-"Multiple"-"Simons-Foundation"-"Prof"-"UNIS" positions at Duke University
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modeling are pluses. Other qualifications include a Ph.D. in Biology, Evolution, Ecology or allied fields and evidence of strong research productivity through publications and participation in conferences
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Systems Modeling. This position focuses on leveraging and developing new equation learning methods, such as Physics-Informed Neural Networks (PINNs), Biologically Informed Neural Networks (BINNs), and
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development of competitive research proposals. • Provide mentorship to graduate and undergraduate students in the lab. Required Qualifications • A Ph.D. in environmental economics, urban economics, public
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invites applications for a full-time Postdoctoral Scholar to join an interdisciplinary research team studying environmental exposures and immune system development in children. The Scholar will work closely
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fellow will play a critical role in developing and scaling automated platforms for long-term mammalian cell culture, including systems for stem cell maintenance and differentiation. These efforts
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chemoproteomics experiments. The postdoctoral associate will be responsible for developing and optimizing custom data analysis and visualization pipelines; and should be prepared to integrate internal experimental
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projects aimed at developing resource responsible, economically viable solutions to challenges in the food production and critical material systems. There will be the opportunity to mentor students, teach
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of development economics combined with field experience in LMICs, ideally experience in one or more of the five focal countries for the research (Kenya, Tanzania, Uganda, India, Ethiopia). DESIRED QUALIFICATIONS
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. Responsibilities include: - Development of new and implementation and modification of existing experimental procedures. - Data preparation and contribution to oral presentations, grant applications, and publication
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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