117 computational-physics-superconductor Postdoctoral positions at Rutgers University
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mammalian or microbial systems, preferred. Familiarity with computational analysis or coding (e.g., R, Python), preferred. Equipment Utilized Physical Demands and Work Environment PHYSICAL DEMANDS: Standing
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interface of bioinformatics, microbiome ecology, and metabolomics, contributing to both computational analyses and laboratory workflows. This position offers the opportunity to lead integrative projects
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process evaluation (e.g., conduct stakeholder interviews, code interview transcripts, archival review) and supporting RCT implementation. Opportunities for professional development include experiences in
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research with young children Experience with computational methods (e.g., Bayesian modeling, drift diffusion modeling, etc.) Equipment Utilized Physical Demands and Work Environment Overview Statement
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. Effective spoken and written English required. High level of computer literacy required. Experience in chromatography (including FPLC and preferably including HPLC) and electrophoresis required. Experience in
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, geography, urban informatics, or a similar field with suitable analytic skills to conduct transportation analysis. The ability to conduct qualitative research and organize and run focus groups is essential
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Experience · PhD in oceanography, atmospheric science, geophysics, economics, computer science, statistics, or a related discipline at time of appointment; · Familiarity with literature relevant to sea-level
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), (2) application of computational approaches and advanced data analysis, (3) optogenetic or viral circuit manipulation, or (4) development of naturalistic rodent behaviors. Equipment Utilized Physical
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the Rutgers High Performance Computing infrastructure. The results of the research will be submitted for publication in a scientific journal. Preferred Qualifications Equipment Utilized Physical Demands and
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required. High level of computer literacy required. Preferred Qualifications In-depth understanding and hands-on experience in RNA-seq and ChIP-seq sample preparation, data collection, and data processing