💼 Role Overview
At Bosch Corporate Research, we develop, examine and enhance new systems, components and technologies. Our aim is simple - improving lives. Around 1700 researchers and engineers work at Bosch worldwide to develop new materials, methods and technologies as well as new systems, components and production processes.
We are seeking a highly motivated and enthusiastic student to join our team as an intern in the field of sustainable HVAC/ thermal systems. This internship focuses on both domain-specific and intelligence development tasks, particularly in data analytics and AI algorithms. The core areas include system-level energy management and system reliability, leveraging AI/ML techniques for data analysis, visualization, and validation.
Successful candidate will be responsible for the following duties within corporate research center in Singapore:
🎯 What you will do (Key Responsibilities)
- Conduct literature research to scout AI and GenAI applications in HVAC systems, with emphasis on enhancing energy efficiency, fault diagnosis, and developing advanced control strategies through data-driven insights.
- Develop intelligent functions using AI/ML techniques to analyze and interpret data, enhance system diagnostics, and optimize control strategies for improved energy efficiency and reliability.
- Integrate software-hardware modules for field testing and validation of developed solutions.
- Collaborate with a diverse team of international researchers, engineers, and fellow interns to advance project goals and translate findings into practical applications.
- Participate in team meetings, discussions, and knowledge-sharing sessions to contribute insights and stay aligned with project objectives.
- Prepare and present project updates, technical documentation, and findings to the team and stakeholders.
👤 What We're Looking For (Qualifications & Skills)
Essential Requirements
- Commitment to a full-time internship of four to six months.
- Currently pursuing an undergraduate or postgraduate degree in Mechanical Engineering, Electrical or Electronic Engineering, Computer Science, Artificial Intelligence, Data Science, or a related field.
- Proficiency in Python, with working knowledge of data science libraries (Pandas, NumPy, SciPy, Scikit-learn, Matplotlib, TensorFlow, or PyTorch).
- Demonstrated competency in exploratory data analysis, statistical analysis, and machine learning techniques applied to real-world datasets.
- Practical experience with time-series and sensor data, including data cleaning, feature engineering, anomaly detection, forecasting, and classification tasks.
- Ability to develop, validate, and interpret data-driven models using appropriate statistical and machine-learning metrics.
- Strong analytical and problem-solving capabilities, with proficiency in troubleshooting data-quality issues and optimising algorithm performance.
- Excellent written and verbal communication skills, with the ability to produce technical documentation, visualisations, and presentations.
- Ability to work both independently and collaboratively within a multidisciplinary, international research team.
Preferred Experience
- Proficiency in C or C++.
- Familiarity with Internet of Things technologies, including connected sensors, device telemetry, data acquisition, and cloud or edge-based data processing.
- Basic understanding of HVAC systems, room air-conditioning, VRF systems, thermodynamics, heat transfer, or building energy systems.
- Exposure to multimodal sensing technologies (temperature, humidity, pressure, occupancy, power, acoustic, or visual sensing).
- Experience with data visualisation tools, dashboards, databases, APIs, or version-control systems.