10 advance-soil-structure-modeling Postdoctoral positions at University of Southern California
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advanced computing applications. The selected candidate will contribute to the design, prototyping, and testing of photonic devices and circuits aimed at enabling next-generation computing architectures
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movements and policy; leads convenings and communications that deepen and broaden our reach into key audiences; engages in strategic collaborations that leverage our strengths for broader impact; and models
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impact; and models an effective, sustainable, and racially-just research institute. For more information about us and our projects, visit: https://dornsife.usc.edu/ERI . This postdoctoral position is
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, experimental studies (in vitro and in vivo), and advanced multiomics data science. We are looking for candidates with expertise or interest in environmental health, biostatistics, and data science, especially as
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within previous five years Minimum Experience: 0-1 year Minimum Field of Expertise: Directly related education in research specialization with advanced knowledge of equipment, procedures and analysis
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Computer Engineering within the USC Viterbi School of Engineering. The ideal candidate will have an extensive background in one or more of the following areas: Information theory, structured statistics
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are committed to promoting diversity, nurturing career advancement, and supporting the future academic autonomy of accomplished candidates. This Postdoctoral Scholar - Research Associate will serve as a key
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. or equivalent doctorate within previous five years Minimum Experience: 0-1 year Minimum Field of Expertise: Directly related education in research specialization with advanced knowledge of equipment, procedures
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advanced knowledge of equipment, procedures, and analysis methods. Percentage of Time: 100% Fixed Term? Yes If Fixed Term (indicate dates): Through 6/30/26 Minimum Education: Ph.D. or equivalent
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generation data-driven stochastic and distributionally robust optimization methodologies or (ii) develop advanced fairness promoting stochastic optimization frameworks. In coordination with Prof. Shehadeh