Researcher: AI/ML enhanced Computational Engineering for Scientific AI and Optimization

The aim is to develop next-generation Scientific ML technologies that enable automatic discovery, refinement, and deployment of interpretable physical models for industrial system simulation. The role will contribute to the long-term development of AI-assisted engineering methodologies, bridging physics-based simulation, symbolic regression, numerical optimization, and Large Language Models (LLMs) for future digital engineering workflows.

You’ll be a part of an innovation team dedicated to transforming engineering simulation through Artificial Intelligence. Our mission is to accelerate virtual product development by combining scientific machine learning, physical modeling, and industrial simulation technologies. Working closely with simulation experts, applied mathematicians, AI researchers, and product development teams across Germany, Spain, India, USA, and China, we develop methodologies that support future digital twins, virtual verification, and AI-assisted engineering design across multiple Bosch business sectors, including Home Appliances, HVAC, Mobility, and Power Tools.

Your responsibilities will involve:

• Research and evaluate state-of-the-art methodologies in Scientific Machine Learning, Symbolic Regression, AI-assisted scientific discovery, and physics-informed AI.

• Develop novel methodologies for discovering governing equations from experimental and simulation data under partial observability and uncertain boundary conditions.

• Advance algorithms for interpretable model discovery, extrapolation, hidden-state inference, and multi-physics equation discovery.

• Nice to have: LLM reasoning, numerical optimization, evolutionary search, and domain knowledge.

• Nice to have: Publish technical papers, patents. Benchmark emerging AI technologies and define technical direction for future feature development.

Educational qualification:

MS/M. Tech, PhD from top Indian institutes (IITs, IISc etc.) or from top international institutes with good track record of research publications related to Mechanical Engineering, Applied Mathematics, Physics, Computer Science, Control Engineering, Scientific Computing, or related disciplines.

Experience : 3 + years of experience

Mandatory/required Skills :

• Strong programming skills in Python for scientific computing and software development, is non-negotiable.

• Solid understanding of computational mechanics/ numerical methods, optimization, and dynamical systems.

  • Profound knowledge and experience of advanced numerical techniques like Finite element, Finite Volume and Finite difference methods etc. If you know only to use numerical methods via simulation tools like ANSYS, ABAQUs, COMSOL, OpenFOAM etc. and don’t have in depth knowledge of the theory behind the methods this is not a right role for you. You should know very well how the traditional numerical methods work as the tasks will be to complement and improve on that using ML methods and not just about using ML methods for problems. So basics on computational mechanics/numerical methods is a must.

• Worked on with Scientific Machine Learning: Symbolic and Sparse Regression, Physics-informed Machine Learning, Operator learning, system identification

• Experience with scientific computing libraries (NumPy, SciPy, SymPy, Pandas, Matplotlib).

• Experience with PyTorch or equivalent machine learning frameworks.

• Git, HPC, cloud computing for scientific workloads

• Strong analytical and mathematical problem-solving skills.

  • Knowledge of ODEs and PDEs and linear algebra.

• Excellent communication skills in English.

• Ability to work independently in interdisciplinary international research teams.

Preferred Skills :

• Nonlinear optimization, Bayesian optimization, Evolutionary algorithms

• Familiar with Large Language Models and AI Agents

• Nice to have Reinforcement learning experiences

Personal Competencies

• Passion for scientific innovation and engineering excellence.

• Strong curiosity toward emerging AI/LLM technologies.

• Ability to bridge mathematics, physics, AI, and industrial engineering.

• Excellent critical thinking and structured problem-solving skills.

• Self-driven, proactive, and comfortable working with open research questions.

• Strong collaboration and communication skills in international environments.

• Willingness to challenge conventional engineering methodologies and contribute to future engineering paradigms.

Why Join Us?

You will help build one of the company's strategic technology capabilities at the intersection of Artificial Intelligence, Physics, and Industrial Simulation.

Your work will directly influence:

• Future simulation methodologies

• AI-assisted engineering design

• Virtual product verification

• Cross-domain engineering applications

• Patent generation and scientific publications

• Strategic collaborations with leading universities and research institutes