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Job Description
The Research Engineer for this AI-accelerated computational fluid modeling project will be responsible for developing and implementing machine learning algorithms to enhance CFD simulations. They will integrate AI models with existing CFD software, conduct computational experiments, and analyze results. The ideal candidate should have a strong background in both machine learning and fluid dynamics, with expertise in programming languages such as Python and C++, and experience with deep learning frameworks like PyTorch or TensorFlow. They will collaborate closely with biomedical engineering and computer science researchers, contribute to research publications, and assist in grant writing.
Qualifications
- Candidate should have at least a Master's degree in Computer Science, Engineering, or a related field, along with excellent problem-solving skills and the ability to work effectively in a multidisciplinary team environment.
- Technical skills:
a. Proficient in Python, C++, and CUDA
b. Experience with deep learning frameworks (PyTorch, TensorFlow)
c. Knowledge of CFD principles and software
- Required experience:
a. Applying AI/ML to scientific computing
b. Fluid mechanics and numerical simulations
c. High-performance computing
- Key soft skills:
a. Problem-solving and analytical thinking
b. Effective communication and teamwork
c. Self-motivation and independence
- Main responsibilities:
a. Develop AI algorithms for CFD acceleration
b. Integrate AI with CFD software
c. Conduct experiments and analyze results
d. Collaborate across disciplines
e. Contribute to publications and grants
- Desirable qualifications:
a. Relevant publications
b. Biomedical fluid dynamics experience
c. Scientific visualization skills
- Open to fixed-term contract
