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wireless networks. For further information about potential research directions, please visit: https://people.cs.vt.edu/boji https://ece.vt.edu/people/profile/liul.html Required Qualifications - Ph.D. in
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candidate will play a key role in developing and advancing new models and simulations for Computational Fluid Dynamics (CFD) hypersonic codes. Specific tasks include developing new turbulence and transition
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background in coding. • Ability to work effectively with a diverse team from multiple disciplines. • Strong communication skills. • Enthusiasm for leading experiments with human subjects. Preferred
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experimental methods for Hypersonic testing facilities • Expertise in one or more optical diagnostics methods for high speed flows • Experience with Hypersonic CFD codes, such as US3D • Proficiency in LabView
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decision-making, with a focus on dopamine neural coding and its dysfunction. Please see: Amo et al., Neuron, 2024 (https://www.cell.com/neuron/fulltext/S0896-6273(23)00979-0 ) Amo et al., Nature Neuroscience
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and networking, with a particular focus on 5G and Beyond 5G technologies and applications of artificial intelligence and machine learning to wireless systems. The candidate will oversee the design and
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. - Strong quantitative skills and experience coding in MATLAB or Python - Track record of publications and presentations. - Experience in mentorship and/or teaching. Preferred Qualifications • Demonstrated