Intern, HVAC Research

Bosch ASEAN; Singapore; On-site; SGD 17,000 - 20,000; Full time

Job summary

Bosch ASEAN in Singapore invites talented students for a 6‑month Internship in HVAC Research. You will gain hands‑on experience in a corporate environment, supporting ongoing projects and learning from experienced professionals.

Key tasks include studying refrigeration cycles, creating physics‑guided models, and developing ML‑based anomaly detection with Python (PyTorch/TensorFlow) and MATLAB. You will prepare technical reports and present findings to stakeholders.

Qualifications

• Full-time internship for 6 months starting Sep/Oct 2026.
• Masters student or recent graduate in relevant engineering.
• Strong knowledge of HVAC, refrigeration cycles, and ML basics.

Responsibilities

• Study HVAC fundamentals and analyze system behavior under faults and anomalies.
• Develop physics-guided models and support simulations to generate data.
• Perform data analysis, feature extraction, and anomaly/detection algorithms.
• Validate diagnostic methods with simulations and experiments.
• Participate in technical discussions on refrigeration, controls, and diagnostics.
• Prepare technical reports and presentations for stakeholders.

Skills

HVAC systems

ML fundamentals

Python programming

Communication skills

Presentation skills

Problem-solving

Education

Master's degree in Mechanical Engineering

Master's in Energy Engineering

Master's in Applied Physics

Tools

Python

PyTorch

TensorFlow

Scikit-learn

MATLAB

Dymola

Job description

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.

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