Job Description
- Job Description:
- Lead the creation of differentiable CFD frameworks in JAX, extending capabilities to complex geometries and non-periodic boundary conditions using immersed boundary methods
- Design, implement, and containerize code (Docker/enroot) to ensure reproducibility and scalability across multi-node GPU HPC environments
- Develop optimized parallel linear solvers (FFT or matrix decompositions) and gradient-based scripts to iteratively modify reactor designs based on catalyst activity
- Rigorously validate simulation accuracy against benchmark results and fixed-bed reactor configurations for both non-reactive and reactive flow regimes
- Partner with AI model developers to integrate property predictions and generate comprehensive technical reports summarizing algorithm scalability and differentiability
- Requirements:
- PhD or MS in Computational Physics, Mechanical/Chemical Engineering, Computer Science, or equivalent
- 3+ years (including PhD) of hands-on experience in CFD code development, specifically on GPUs
- Proven ability to build scalable software on multi-GPU systems using JAX, PyTorch, CUDA, or MPI frameworks
- Full fluency in numerical linear algebra, PDE numerical methods, sparse/dense linear solvers, and immersed boundary methods
- Excellent Python programming skills, with JAX proficiency as a prerequisite
- Ability to manage multiple deliverables and produce clear technical documentation for milestone reviews
- Benefits:
- Comprehensive medical, dental, and vision coverage for employees and dependents with generous employer premium contributions
- Retirement savings with company matching
- Paid parental leave
- Inclusive family-building benefits
- Flexible paid time off
- Company-wide seasonal breaks
- Support for flexible work arrangements that enable sustainable performance
- Opportunities for continuous learning and growth through on-the-job development, cross-functional collaboration, and access to internal learning and development programs
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