Researcher: AI/ML enhanced Computational Engineering for Scientific AI and Optimization
Bosch (Robert Bosch LLC) (company site, opens in a new tab)BengaluruOn-siteDirect career pageEst. 25–45 LPA
Posted on 31 Aug
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Job description
Structured overview of role & requirements
About This Role
- Research and develop AI-assisted engineering methodologies integrating Scientific Machine Learning, physics-based simulation, and numerical optimization for industrial system simulation.
- Advance algorithms for interpretable model discovery, extrapolation, hidden-state inference, and multi-physics equation discovery using experimental and simulation data.
- Collaborate with international teams to transform engineering simulations and support digital twins, virtual verification, and AI-assisted engineering design in multiple Bosch business sectors.
Minimum Requirements
- MS/M.Tech or PhD in Mechanical Engineering, Applied Mathematics, Physics, Computer Science, Control Engineering, Scientific Computing or related disciplines from reputed institutes (IITs, IISc, or top international institutes).
- Strong programming skills in Python for scientific computing; experience with NumPy, SciPy, SymPy, Pandas, Matplotlib, and PyTorch or equivalent ML frameworks.
- Experience with Scientific Machine Learning methods including Symbolic Regression, Physics-informed Machine Learning, Neural Operators.
- Work Experience Required: Not explicitly mentioned in the JD.
Ideal Candidate Profile
- Experienced in bridging interdisciplinary domains: mathematics, physics, AI, and industrial engineering with a focus on scientific AI technologies for engineering simulation.
- Comfortable working independently in international, interdisciplinary research teams with strong analytical and communication skills in English.
- Strategically aligns with innovation in AI, numerical optimization, symbolic regression, and emerging technologies such as LLMs to influence future digital engineering workflows.