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pressing challenges. The PIIRS Postdoctoral Fellows Program is integral to that mission. We will award two postdoctoral fellowships to our 2026-27 cohort. PIIRS seeks recent PhDs in the Social Sciences who
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-friendly tools that will be used by a broad community. The scope of the work builds on recent publications from the laboratory, e.g. integrating language models with mass spectrometry data (https
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retrotransposition using an integrated biochemical and structural approach with a focus on cryo-EM. The postdoctoral scholar will have access to cutting-edge cryo-EM instrumentation and computational resources through
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. Christopher Emrich at the University of Central Florida. The appointment will be through Princeton's School of Public and International Affairs. The research position requires a PhD in a relevant field (e.g
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following areas: alternative cements (e.g., chemistry of calcium silicate and carbonate cements), physics of diffusion and carbonation, early-stage rheological characteristics, life cycle analysis, and design
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position. Applicants should have a PhD degree (or expect to receive a PhD degree by June 15, 2025) in Psychology or allied fields (e.g., Sociology) with an interest in conducting research relevant to racial
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in different brain models (tree shrew, macaque, human neurotypical, schizophrenia patients) and levels of analyses (local- and large-scale circuits). This is a unique opportunity to learn about team
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subdivisions of the squamate body plan. The candidate will work towards developing computational resources that assist in the data management and analysis of genomic data and its integration with phenotypic data
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candidates with strong expertise in building and conducting ultrafast time-resolved optical experiments. Key skills include the ability to design, assemble, and align ultrafast optical setups, integrate setups
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-Sigler Institute for Integrative Genomics and the Computer Science Department at Princeton University. We seek candidates with computational biology, bioinformatics, computer science, machine learning