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modeling approaches. • Investigate interactions between food products and paper-based packaging materials across diverse product categories. • Collect, process, and analyze experimental data, including
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and distribution systems, including unit load design and supply chain efficiency. • Collect, process, and analyze experimental data from mechanical testing equipment; prepare technical reports and
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elements • Design and perform long-term laboratory testing on thermally modified wood CLT assemblies with various protective coatings. • Collect, process, and analyze experimental data; prepare technical
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Department at #2 nationally in the Electrical and Electronic Engineering category. Required Qualifications • PhD degree in Electrical Engineering, Computer Engineering, or other related disciplines. PhD must
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for construction operations. The successful candidate will contribute to cutting-edge research in mixed reality (MR)-based simulation platforms, machine learning-based process optimization, and human-machine
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opportunities. Required Qualifications • Ph.D. in neuroscience or related discipline. PhD must be awarded no more than four years prior to the effective date of appointment with a minimum of one year eligibility
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include in vitro neural differentiation, gene expression manipulation, metabolic assays, and mouse breeding and behavior. Knowledge in basic computer skills, record keeping and experience with data
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jurisdictions utilizing land use-value assessment estimates. Duties include, but are not limited to: development of computational methods, maintenance of current models and data sets, identifying and testing
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. The Postdoctoral Associate is expected to lead research projects from experimental design, data analysis, to presentations in lab meetings, conferences, and seminars, as well as prepare manuscripts for peer-reviewed
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Analysis: Process and analyze neural and behavioral data (custom coding required). • Stereotaxic Surgery: Conduct precise stereotaxic injections and implants in mice. • Transgenic Mouse Colony Management