**Job Description**
The School of Mechanical & Aerospace Engineering (MAE) is seeking a part-time research assistant to develop next-generation computational tools for simulating two-phase flows. This involves integrating advanced Artificial Intelligence (AI) techniques with traditional computational fluid dynamics (CFD) methods, specifically transitioning legacy CFD solvers to modern, Python-based AI frameworks like PyTorch and JAX. The role aims to achieve high-efficiency, scalable simulations of water-air systems transport, targeting up to 50x speedups for real-time, energy-efficient modeling of complex multiscale flow phenomena relevant to coastal engineering. The successful candidate will contribute to an AI-optimized platform, advancing AI-augmented fluid dynamics and delivering an open, sustainable simulation tool for the research and engineering community.
**Skills & Abilities**
• Strong critical thinking and problem-solving skills
• Effective communication, teamwork, time management, and self-motivation skills
• Strong foundation in CFD
• Proficiency in Python and AI/ML techniques
• Experience in parallel computing tools such as CUDA and MPI
• Experience with CFD simulation tools (e.g., OpenFOAM, Ansys Fluent) is advantageous
• Capable of developing novel computational strategies beyond traditional CFD paradigms
• Enthusiastic about exploring and applying emerging AI techniques to engineering challenges
**Qualifications**
Required Degree(s) in:
• Mechanical Engineering
• Computational Science
• Applied Mathematics
• A related field
**Experience**
Other:
• Strong track record of peer-reviewed publications in relevant fields
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