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and machine learning to optimize treatment conditions. Contribute to the development of reproducible stress priming methods and assist in transferring knowledge to agricultural stakeholders. Required
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design, enabling timely analysis during design cycles. These components significantly impact engine/airframe integration and fuel burn, making efficient design methods essential for optimizing overall
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Stimulated Raman Spectroscopy (PARS) method. Research tasks will include design, development and optimization of the full PARS system including a Raman cell pumping scheme, a photoacoustic cavity, and an
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& design, catalyst design & modelling, and carbon capturing & conversion. Proficiency in fluidized reactor design & optimization, hydrodynamics & molecular dynamics modelling (openFOAM, Ansys Fluent, LAMMPS
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responses. The successful candidate will work at the interface of viral vector development and cancer immunology, contributing to NIH-funded projects involving VSV platform optimization, immune modulation
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to create new designs that optimize water yield. The project aspires to elucidate the physics governing droplet impact and wetting on fibrous networks in order to enhance fog net technology. The planned work
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themes are not covered, including conventional medical imaging). Examples include Bayesian optimization for molecular or materials design; machine learning for single cell data; physics-based ML
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themes are not covered, including conventional medical imaging). Examples include Bayesian optimization for molecular or materials design; machine learning for single cell data; physics-based ML
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, including conventional medical imaging). Examples include Bayesian optimization for molecular or materials design; machine learning for single cell data; physics-based ML for turbine design and
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, including conventional medical imaging). Examples include Bayesian optimization for molecular or materials design; machine learning for single cell data; physics-based ML for turbine design and