80 algorithm-development-"Multiple"-"Prof"-"UNIS" Postdoctoral positions at Princeton University
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researchers working on an NIH funded project focused on developing new systems models to examine social and biological drivers of infection inequality. The overarching goal of this postdoctoral position is to
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discovery. The successful candidate will develop new, openly accessible datasets and machine learning models for modeling redox-active solid-state materials. Candidates who are nearing completion
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The Department of Electrical and Computer Engineering has opening for postdoctoral research positions in the following fields: 1. Microfluidic and Lab-on-Chip development in a multidisciplinary lab
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addition to the aforementioned project, the appointee will have opportunities to develop additional projects with members of Dr. Sinclair's lab and/or maintain their on-going work. The work location for this position is in-person
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University community. This mission is pursued and supports the University's purpose by using current knowledge of health and human development to guide responsive, high quality clinical, prevention, and
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days per week. Leveraging Princeton's scholarly resources, fellows will focus on research, expand their intellectual horizons, and prepare work for publication. They will have biweekly meetings with
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position for new projects to characterize synthesis processes and novel materials in several research thrusts: i) development of advanced manufacturing processes for low-cost battery cathode active materials
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indirectly support DDSS-supported projects or its mission. Candidates will be able to apply and further develop their technical skills in a dynamic research environment. The successful candidate will have the
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-assembly, and soft condensed matter. The successful candidates will develop computer simulation approaches to understand compartmentalization inside cells (i.e., formation of biomolecular condensates) and to
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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