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Field
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objects, by embedding them into a 2 or 3-dimensional space through a representation learning algorithm, has been widely used for data exploratory analysis. It is particularly popular in areas such as
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of New Hampshire invites applications for a non-tenure-track Assistant Research Professor position in Sustainable Engineering. We seek applicants with a strong background in systems analysis and simulation
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, including large-scale data analysis, alpha signal research, and strategy performance enhancement. While there is some overlap with the Quantitative Systematic Trader role, Quantitative Researchers typically
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qualifications Documented experience with data analysis and programming (e.g., Matlab, Python or R). Experience of risk assessment and/or decision analysis Experience of probabilistic methods such as Monte Carlo
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approach including empirical data analysis, experiments, and theoretical modelling to develop science-based management strategies for the restoration of woodland ecosystems. We will collect, and collate from
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* experience writing peer reviewed publications. Experience working in multi-disciplinary teams. Significant* experience setting up custom experiments for data collection and analysis. Experience developing and
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. This project is intended to perform numerical studies and develop a methodology for the numerical analysis aimed at the effective damping of resonance regimes in bladed disks of gas-turbine engines using
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data analysis, alpha signal research, and strategy performance enhancement. While there is some overlap with the Quantitative Systematic Trader role, Quantitative Researchers typically focus more on
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of diverse, deformable textiles at cycle times below one second, while hyperspectral, NIR, Raman, and RGB sensors feed an edge-compute AI pipeline for real-time decision making that routes each item
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new cures to the world's deadliest diseases and make life beyond cancer a reality. At Fred Hutch we value collaboration, compassion, determination, excellence, innovation, integrity and respect. Our