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Tier-1 employer in Bangalore but highly specialized PhD-level research reduces applicant density.
Role demands domain-specific physics, numerical methods, and scientific-ML expertise, limiting cross-industry transferability.
Requires PhD/MS from top institutes and specific scientific-ML, numerical, and PyTorch skills, so filtering is strict.
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Develop and advance AI-assisted engineering methodologies integrating physics-based simulation, symbolic regression, numerical optimization, and LLMs for industrial system simulation.
Research and create novel Scientific AI methods to discover governing physical equations from experimental and simulation data under uncertain conditions.
Guide technical direction by benchmarking emerging AI technologies and collaborating internationally across multiple Bosch business sectors.
MS/M.Tech or PhD from top Indian or international institutes in Mechanical Engineering, Applied Mathematics, Physics, Computer Science, Control Engineering, or related fields.
Strong programming skills in Python for scientific computing, including experience with NumPy, SciPy, SymPy, Pandas, Matplotlib, and machine learning frameworks like PyTorch.
Experience with Scientific Machine Learning techniques such as Symbolic Regression, Physics-informed Machine Learning, and Neural Operators.
Work Experience Required: Not explicitly mentioned in the JD
Experienced in interdisciplinary research bridging AI, physics, and industrial engineering for simulation and design workflows.
Comfortable working independently and collaborating across international, interdisciplinary teams with a track record of research outputs preferred.
Technically proficient in numerical methods, optimization, and scientific computing, with familiarity in emerging AI technologies such as LLMs, evolutionary algorithms, and reinforcement learning as advantageous.