Working Student – Battery Science and Data (f/m/d)

Job description

**About Munich Electrification** Munich Electrification is an innovative company founded with the aim of accelerating the transition to electric and connected mobility. We develop innovative electronic control units for electric vehicles and stationary storage systems for our global customers. Our international team is composed of highly motivated and exceptional engineers. As a small and specialized team we are well-aware of the importance of each individual colleague and support and promote each employee according to their abilities and needs. Our office with adjacent prototype and testing lab is located in the heart of Munich at the Heimeranplatz. This is what we stand for: - **Technological Leadership**: We challenge norms, innovate quickly, and anticipate future needs. We take smart risks and learn from outcomes to stay ahead. - **Sustainability**: We actively drive change for a sustainable future, aware of our impact and inspiring others to build a better world. - **Team Culture**: We believe work should be enjoyable, fostering a spirit of inspiration, celebration, and teamwork across the globe. - **Entrepreneurial Spirit**: We embrace change, think big, and push limits with passion. **Your role** We are looking for a working student to join our Battery Science and Data team. You will work directly with our engineers to gain hands-on experience in physics-based modeling, data analysis, and cloud- based simulation. This is your chance to deepen your knowledge of electric vehicle batteries and the simulation frameworks used to model their real-world behavior. We are hiring several working students for different areas in our team. You will focus on one of them, so you do not need to bring the full list below. Just show us where your strengths are. **Your future tasks at a glance** - Support the development and validation of battery cell models and high-level algorithms (e.g., SOx estimation) by running simulations and analyzing results. - Help build and maintain our cloud data platform by structuring raw IoT logs, designing data models, and improving time-series storage as well as query performance. - Support the team with deployments in test cars and monitor OTA (Over-the-Air) updates to ensure data integrity. - Evaluate, implement, and document proof of concepts for future algorithms or new data analysis tools. **What you bring with you** - Student in electrical engineering, physics, mathematics, computer science, software engineering, or a similar field. - Confident working in a high-level programming language (Python preferred). - Basic understanding of general electronics, embedded systems, and IoT devices. - Willingness to take responsibility for a project and not to be discouraged by setbacks. - Preference for working in teams and strong communication skills (English and German preferred). - Ideally, you also have Experience with at least one of: data analysis in Python, databases (SQL / time-series) or cloud/infrastructure tooling (AWS, Docker, Git). - Knowledge of dynamical systems (ODEs) or state estimation methods (e.g., Kalman filters). - Initial insights into modeling lithium-ion battery behavior. - Exposure to machine learning frameworks. **Our Offer & Benefits** The chance to be part of a highly innovative, agile, and unique team with prestigious customers in the automotive and battery storage sector. You will gain a deeper knowledge around connected & electric vehicle batteries, battery management and electronics development and strive in an exciting work environment **Benefits (Full-time Employees):** - Trust-based working hours and hybrid work - Adequate and competitive compensation - Pension Plan/Bonus - Free access to the fitness center right next to us or subsidized EGYM Wellpass - Free snacks, coffee, drinks and lunch (freshly cooked by our chef) every day - Public transport ticket - Bike-Leasing via Business Bike - Experience various inspiring and fun team events - ME-branded clothing - Option to "work from anywhere" (6 weeks/year)