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-based metal additive manufacturing . The role will focus on thermal field modelling, multi-physics numerical simulations, machine learning and process parameter optimization. We expect the candidate
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thermodynamic and kinetic models into an alloy design framework (including material properties models) that uses numerical optimization methods to rapidly screen for promising compositions over vast multi
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Position Summary The successful candidate will work with Dr. Kunlun Qi < https://kunlun-qi.github.io > on research projects related to kinetic equation and its related multiscale model reduction
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CFD Experience with low fidelity modeling of aerodynamics Experience with numerical optimization Proficient in Python and the various numerical packages Ability to work both independently and as a
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Optimization: Resolving hardware-specific performance and numerical precision challenges across diverse GPU environments. Architecture Design: Leading the design of new loss functions, model architectures
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dynamics and large-scale numerical modeling of semiconductor laser arrays at the College of Optics and Photonics (CREOL), University of Central Florida. Our research program investigates collective
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year, with the possibility of renewal for more years, subject to the performance and the availability of funding. The successful candidate will work with Dr. Kunlun Qi < https://kunlun-qi.github.io
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sustainability-driven optimization of hybrid multi-material structures. The work focuses on bringing environmental and circularity goals into structural design alongside strength, stiffness, and cost
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learning (e.g., deep learning, optimization, or learning theory) Programming skills in Python and experience with scientific computing (e.g., NumPy, SciPy, PyTorch) Experience with numerical
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learning (e.g., deep learning, optimization, or learning theory) Programming skills in Python and experience with scientific computing (e.g., NumPy, SciPy, PyTorch) Experience with numerical