PhD candidate specializing in Data Science & Machine Learning at BMW Group, focusing on innovative solutions for electric vehicle charging infrastructure.
Responsibilities
Develop AI-supported methods for automated analysis and fault attribution using communication and vehicle data across the entire charging ecosystem.
Work with real BMW charging data, communication protocols, and ISO/IEC standards.
Define and implement use cases for fault detection, anomaly analysis, and quality assessment of DC charging sessions.
Prepare scientific contributions to advance international e‑mobility standards.
Develop predictive and preventive optimization measures to be integrated into BMW systems (e.g., eRoute) and customer-facing features.
Collaborate with internal departments and a university, and present results in both academic and industrial forums.
Requirements
Master’s degree in Computer Science, Electrical Engineering, Data Science, or a comparable technical discipline.
Solid knowledge of AI methods (e.g., deep learning, clustering, anomaly detection) and practical experience with Python or comparable frameworks.
Interest in automotive communication standards (e.g., ISO 15118) and data-intensive technical systems.
Willingness to make research results visible in both academic contexts and BMW corporate practice.
Benefits
Comprehensive mentoring & onboarding.
Personal and professional development opportunities.
Flexible working hours.
Mobile/remote work.
Attractive and fair compensation.
Annual additional payments such as holiday and Christmas bonuses.
Student apartments (subject to availability; Munich location only).
Job title
PhD Candidate Data Science, Machine Learning – Electric Vehicle Charging Infrastructure
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