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interested in computational materials design and discovery. The successful candidate will develop new, openly accessible datasets and machine learning models for modeling redox-active solid-state materials
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polymer physics. The successful candidate will develop strategies to design, synthesize, and characterize the properties of soft materials using advanced microscopy techniques and related methods
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, with emphasis on HRXPS, LEIS, AES, LEED, TPD, HREELS, Raman scattering, and SEM. Qualified candidates should possess experience for the design, construction, operation, and maintenance of UHV instruments
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The Rosen Research Group at Princeton University (https://rosen.cbe.princeton.edu) is searching for a postdoctoral or more senior researcher interested in computational materials design and
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, or a related field and must have less than three years of post-PhD research experience prior to anticipated start date. Applicants must apply online at https://puwebp.princeton.edu/AcadHire/position
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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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model output available to a diverse audience. Candidates must have a PhD in computer science, environmental and physical sciences, or a closely related field. The following attributes are desirable: a
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you will be asked in the application which positions you are interested in. For further inquiries, contact astropd@princeton.edu. PhD is required. The work location for this position is in-person
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of whole genomic data already available; and ii) investigating rates of evolution across the genome and their correlation with phenotypic traits across various subdivisions of the squamate body plan
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leading and mentoring graduate and undergraduate students. A PhD in relevant fields of energy storage, electrochemistry, and materials characterization is required. Experience with solid electrolytes