HVAC Research Intern: ML-Driven Diagnostics & Modeling

Bosch ASEAN

Singapore

On-site

SGD 17,000 - 20,000

Full time

18 hours ago
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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

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.

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