Research Engineer: Modelling and Simulation for Real-time Connected mobility and Industrial Control Systems

Company Description

At Bosch Research, research meets application. Around 1,700 experts around the world develop the technologies of tomorrow and beyond. The world in which we live is changing rapidly. Global megatrends such as climate change and digitalization influence virtually every area of day-to-day life. One thing that doesn’t change is Bosch’s mission to create technology that is “Invented for life” in other words using technological innovations to improve people’s quality of life and using natural resources responsibly. Bosch Research sees itself as the spearhead of innovation at Bosch: Our researchers are involved in around a quarter of the patent applications filed by Bosch. On the one hand, we help all Bosch divisions to develop the next generation of products or the generation after that. On the other hand, we look far into the future: with our partners in science and industry, we identify technologies and trends which will shape our lives in the future and make them usable for the entire company. As a global team with around 1,700 experts from all over the world, we cover a wide range of areas with our research. Whether it be automation, digitalization and connectivity, artificial intelligence (AI), electrification, climate action and sustainability or healthcare: Bosch Research combines top-level research with specific technological developments.

For more information visit: https://www.bosch.com/research/

The Research and Technology Center at Bangalore focuses on research in Real-time connected mobility and industrial control systems and Hybrid modelling (system modelling using a combination of physics and AI/ML), Time series analysis, Natural language processing, Computer vision, GenAI applications, Numerical methods, Embedded real time systems, We pursue research and development by working with top-tier universities worldwide and our corporate partners.

Job Description

The focus is set on developing advanced algorithms and strategies for control of real-time connected mobility and industrial control systems. This role requires you to have deep knowledge of numerical methods, modelling and simulation techniques for ODEs and PDEs(ordinary and partial differential equations), along with very clear understanding of control systems and Machine learning & Artificial Intelligence which you’ll leverage to model and simulate real-time applications connecting multiple embedded, edge and cloud devices and synthesize control functions for them. You will:

• Build physics or AI/ML based surrogate models for the control systems of interest and quantify and propagate parameter and timing uncertainties through the system in simulation,
• Synthesize control functions with good quality of control that are tolerant of delays and other parameter uncertainties, using physics based or AI/ML based techniques as per requirements,
• You’ll work in international teams and perform necessary research, development/implementation to accomplish the tasks,
• Further Publish research findings in reputable journals and conferences.

Qualifications

Educational qualification:

MS/M. Tech from top Indian institutes (IITs, IIITs, IISc etc.) in the field of Electronics and Communication Engg, Electrical Engg, Mechanical Engg, Mechatronics Engg, Aerospace Engg, Computer Science Engg, from top international institutes with good academic track record.

Experience :

3+

Mandatory/requires Skills :

Solid engineering background with proficiency in Mathematics.

• Good knowledge on Ordinary and Partial Differential equations.
• Sound knowledge of numerical methods for modelling and simulation.
• Sound understanding of Linear algebra, Matrix theory.
• Knowledge of control theory
• Excellent programming skills in python.
• Excellent presentation and communication skills.
• Knowledge of local and global parameter optimization methods

Preferred Skills :

• Experience with simulation tools: MATLAB, Simulink, C, C++ will be added advantage.
• Knowledge of modern control theory
• Familiarity with high performance computing will be added advantage.
• Understanding of concepts in uncertainty quantification