Bosch ASEAN
Intern, HVAC Research
Skills
7 days ago
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Important information
Contract type:
Permanent
Location:
Singapore
Work mode:
Onsite
Published on:
21 October 2026
What they need
Your tasks
💼 Role Overview We are looking for a motivated and enthusiastic individual to join Bosch for a fulfilling internship opportunity! This internship will provide valuable hands-on experience in a corporate environment, allowing you to contribute to ongoing projects while learning from experienced professionals. As a Intern HVAC Research you will support the operations and learning initiatives in collaboration with experienced team members.
🎯 What You Will Do (Key Responsibilities)
- Study refrigeration cycle fundamentals and analyze HVAC system behavior under various operating conditions, fault scenarios, and anomalies including refrigerant charge deviations, airflow disturbances, and sensor abnormalities.
- Develop first-principles and physics-guided models to characterize normal and abnormal system operation, and support simulation studies and experimental investigations to generate operational datasets.
- Perform data analysis, feature extraction, and develop anomaly prediction and diagnostic algorithms using engineering knowledge combined with machine learning techniques.
- Validate diagnostic methodologies using simulation and experimental results.
- Participate in technical discussions on refrigeration systems, controls, and system diagnostics.
- Prepare technical reports, research presentations, and project demonstrations for stakeholders.
Your profile
👤 What We're Looking For (Qualifications & Skills)
- Able to work full-time for a period of 6 months (Sep/Oct 2026 onwards)
- Currently pursuing or recently completed a master's degree in Mechanical Engineering, Energy Engineering, Applied Physics, or a related discipline
- Strong knowledge of HVAC systems, refrigeration cycles, controls, and Machine Learning fundamentals including anomaly detection and predictive modeling
- Proficiency in Python with experience in AI/ML frameworks (PyTorch, TensorFlow, Scikit-learn) or technical computing environments (MATLAB, Dymola)
- Self-motivated with strong problem-solving, communication, and presentation skills
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