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thereafter. The position is for one year initially and may be renewed for up to two additional years, contingent upon funding and mutual agreement. The candidate will work closely with Professor Le Xie as he
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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, 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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many-body physics, spin dynamics, quantum simulation, quantum optimal control, quantum optics, atomic physics. Required Skills: PhD in a field of research related to experimental quantum physics Broad
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Development: Ability to design and optimize AI/ML models for neuroscience. Scientific Writing & Communication: Ability to publish research and present findings. Basic knowledge of neuroscience Ability to work
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research across NIH and the federal government to foster knowledge and optimize health across the lifespan. What will I be doing? As a fellow, you will collaborate with NIH scientists on an evolving area of
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exploring new materials, technologies, and fabrication techniques to enhance the performance, flexibility, and scalability of health monitoring systems. The Research Fellow will collaborate with
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are included but clinical medical themes are not covered, including conventional medical imaging). Examples include Bayesian optimization for molecular or materials design; machine learning for single cell data
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lead research on next-generation solar harvesting materials, focusing on developing and optimizing synthesis methods for novel inorganic nanoparticles and quantum dots designed for solar-to-energy