Researcher: Uncertainty Quantification & Surrogate Modelling at Bosch Group

, karnataka, India -

Full Time

Start Date

Immediate

Expiry Date

22 Mar, 26

Salary

0.0

Posted On

22 Dec, 25

Experience

2 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Uncertainty Quantification, Applied Mathematics, Statistics, Computational Engineering, Aerospace Engineering, Computer Science, AI/ML Techniques, Programming, Python, C, C++, Machine Learning, Deep Learning, System Identification, Dynamical Systems, Numerical Methods, Linear Algebra

Industry

Software Development

Description

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), generative artificial intelligence (Gen 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, computational engineering, hybrid modelling (system modelling using a combination of physics and AI/ML), time series analysis, natural language processing, computer vision, Gen AI 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 Roles & Responsibilities : The focus of this role is set on Uncertainty Quantification (UQ) for model-based system design You’ll have to model parameter uncertainties in order to guarantee best performance under all operating conditions for modern control system applications on distributed compute architectures. You’ll have to analyze and enrich complex system models using uncertainty quantification techniques, AI/ML and surrogate modelling methods and implement everything via the necessary scripting and programming. You’ll enable Bosch products to leverage new distributed deployments while meeting the requirements. You’ll be working in international, multi-disciplinary teams and perform necessary tasks to accomplish the project goals. You’ll publish research findings in reputable journals and conferences. Qualifications Educational qualification: PhD from top Indian institutes (IITs, IIITs, IISc etc.) or from top international institutes with good track record of research publications related to: - Applied Mathematics, Statistics, Computational Engg, Aerospace Engg, Computer Science or any other branch where the candidate has deep expertise in Uncertainty Quantification, Applied Mathematics and AI/ML techniques. Mandatory/requires Skills : Excellent programming skills in python, C, C++ Excellent knowledge of uncertainty quantification Expertise in AI such as machine learning / tabular foundation models / deep learning Expertise in system identification Sound fundamentals of dynamical system Sound fundamentals of ODEs, PDEs and numerical methods for solving them for various engineering problems Sound fundamentals of Linear algebra Excellent presentation and communication skills Preferred Skills : Working knowledge on control systems and engineering will be an added advantage Experience in modern distributed systems architectures e.g. cloud/edge/E/E-architecture will be an added advantage Experience with simulation tools: MATLAB, Simulink and Amesim will be added advantage. Experience in agile working environment preferably Scrum Master certification will be an added advantage Legal Entity: Bosch Global Software Technologies Private Limited

Responsibilities

The role focuses on Uncertainty Quantification for model-based system design, requiring the modeling of parameter uncertainties to ensure optimal performance in control systems. The researcher will analyze and enhance complex system models using UQ techniques, AI/ML, and surrogate modeling methods.