Desay SV, one of the leading mobility technology companies, is committed to be the preferred partner in mobility transformation. Desay SV’s core business focuses on the efficient integration of the three major areas of smart cabin, smart drive, and smart service. We continue to develop highly integrated leading hardware and software algorithms to provide global customers with safe, comfortable, and efficient mobility solutions and services.

Project Background:

During the internship, student will work on data-driven vehicle dynamics for simulation, this is an exciting and rapidly growing field in the automotive industry. The use of data to simulate vehicle behaviour has revolutionized how engineers and developers design, test, and optimize vehicles. By integrating real-world data into simulation environments, manufacturers can more accurately predict vehicle performance and fine-tune dynamics before physical prototypes are built.

We are looking for an enthusiastic Navigation Software Engineer Intern to support our efforts in developing data-driven control methods for vehicle dynamics. The intern will focus on system identification and dynamic model development, working closely with our control systems and simulation teams. You will be involved in processing and analyzing vehicle data, designing algorithms, and integrating models into our control framework.

Scope:

Students will work on the following:

Data Analysis & Preprocessing: Gather, clean, and preprocess vehicle dynamics data from various sources to support system identification tasks.

• System Identification & Model Development: Apply system identification techniques to develop mathematical models of vehicle dynamics. Convert and validate these models using simulation tools.
• Algorithm Development: Write algorithms in Python for model development, data analysis, and integration of control methods. Work with C++ to enhance and deploy models.
• Integration & Testing: Collaborate with the team to integrate the developed models into our navigation and control framework. Assist in setting up tests and analyzing performance.

Requirements:

Students should possess the following:

• Bachelor or Master degree in Computer Science, Electronics and Electrical Engineering.
• Familiar with C++ and MATLAB.
• Understanding of machine learning techniques, especially as applied to data-driven control methods.
• Experience with simulation tools and real-time systems.
• Basic knowledge of control theory and system identification methods.