Part-Time Research Assistant (Machine Learning and Computational Fluid Dynamics)
Part-Time Research Assistant (Machine Learning and Computational Fluid Dynamics)
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Job Description
The School of Mechanical & Aerospace Engineering (MAE) is a robust dynamic and multi-disciplinary international research community comprising of world-class scientists and bright students. MAE prides itself in its excellent research capabilities in areas including advanced manufacturing aerospace biomedical energy industrial engineering maritime engineering robotics etc. The school is equipped with state-of-the-art research infrastructure housing a comprehensive range of cluster laboratories test bedding facilities research centres/institutes and corporate laboratories. Cutting-edge research in MAE addresses the immediate needs of our industries and supports the nations long-term development the new era of industrial 4.0 and sustainable living MAE is rigorous in developing new competencies to support the growth and competitiveness of our engineering sector in the global landscape. MAE has grown to be leader in Engineering Research ranking amongst the top engineering schools in the world.
Key Responsibilities:
Development of AI-augmented CFD frameworks
Simulation two-phase flows
Valid the numerical model with experimental or existing numerical work
Engage in interdisciplinary collaboration
Job Requirements:
Bachelor degree or higher in Mechanical Engineering Computational Science Applied Mathematics or a related field.
Strong in critical thinking and problem-solving with effective communication teamwork time management and self-motivation skills
Strong foundation in CFD with proficiency in Python and AI/ML techniques and additional experience in parallel computing tools such as CUDA and MPI
Experienced with CFD simulation tools (e.g. OpenFOAM Ansys Fluent) is advantageous
Strong track record of peer-reviewed publications in relevant fields.
Capable of developing novel computational strategies beyond traditional CFD paradigms with a strong enthusiasm for exploring and applying emerging AI techniques to engineering challenges.
Capable of proposing and implementing novel computational strategies that go beyond traditional CFD paradigms
Enthusiastic about exploring new AI paradigms and applying them to engineering challenges.
Be able to work at least 2 days each week
We regret to inform that only shortlisted candidates will be notified.
Hiring Institution: NTUEmployment Type
Part-Time
