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collaboration. Required Qualifications - Ph.D. in Forest Products, Forestry, Natural Resources, Sustainability, or a related field. PhD must be awarded no more than four years prior to the effective date
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systems. • Develop and implement predictive models for packaging performance using machine learning approaches and physics-based simulations. • Investigate logistics optimization strategies for packaging
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or, preferably, scientific machine learning (SciML). • Conducting research related to the improvement of the hygrothermal properties of cross-laminated timber. Desing and perform testing and analysis crate
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in areas related to quantum information theory, quantum error correction, and machine learning. The position will start in fall 2026 and will be for two years, with a possible 1-year extension pending
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, fluorescence in situ hybridization, and bioinformatics. Preferred Qualifications Molecular biology and genetics laboratory experience; web computer skills; ability to learn new techniques and procedures
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orientation, or military status, or otherwise discriminate against employees or applicants who inquire about, discuss, or disclose their compensation or the compensation of other employees or applicants