Sustainable HVAC AI Intern: Data, Energy & Diagnostics

Bosch Building Technologies Europe; Singapore; On-site; SGD 13,000 - 20,000; Full time

Job summary

Bosch Corporate Research in Singapore invites an enthusiastic intern to explore AI/ML applications in sustainable HVAC/thermal systems. You will analyze data, develop intelligent functions, and validate solutions through software-hardware integration within a multinational research team.

The role emphasizes literature review, data-driven modeling, and clear communication of findings to stakeholders, with a focus on energy efficiency and reliability. Four to six months commitment required.

Qualifications

• Currently pursuing an undergraduate or postgraduate degree in Mechanical Engineering, Electrical or Electronic Engineering, Computer Science, AI or Data Science.
• Proficiency in Python with data science libraries (Pandas, NumPy, SciPy, Scikit-learn, Matplotlib, TensorFlow, or PyTorch).
• Experience with time-series and sensor data, data cleaning, feature engineering, anomaly detection, forecasting and classification.
• Strong analytical and communication skills, ability to document and present findings.

Responsibilities

• Conduct literature research on AI/GenAI in HVAC for energy efficiency and fault diagnosis.
• Develop intelligent functions using AI/ML to analyze data and optimize control strategies.
• Integrate software-hardware modules for field testing and validation.
• Collaborate with international researchers and interns to advance project goals.
• Prepare project updates, technical documentation and presentations.

Skills

Python

Pandas

NumPy

SciPy

Scikit-learn

TensorFlow

PyTorch

Data visualization

Data quality

Communication

Education

Mechanical Engineering

Electrical Engineering

Computer Science

Artificial Intelligence

Data Science

Tools

C/C++

Edge computing

Job description

Bosch Corporate Research in Singapore invites an enthusiastic intern to explore AI/ML applications in sustainable HVAC/thermal systems. You will analyze data, develop intelligent functions, and validate solutions through software-hardware integration within a multinational research team.

The role emphasizes literature review, data-driven modeling, and clear communication of findings to stakeholders, with a focus on energy efficiency and reliability. Four to six months commitment required.