Intern, HVAC AI Research

Bosch ASEAN; Singapore; On-site; SGD 13,000 - 20,000; Full time

Job summary

Bosch ASEAN in Singapore invites a motivated student to join our Corporate Research team as an intern in sustainable HVAC and thermal systems. You will work on data analytics and AI algorithms to improve energy efficiency, system reliability, fault diagnosis, using AI/ML for data visualization and validation.

You will collaborate with international researchers and engineers, develop data-driven models, present findings, and contribute to cross-disciplinary projects within a corporate research

Qualifications

• Full-time internship of four to six months.
• 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.

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.

Skills

Python

Pandas

NumPy

Scikit-learn

TensorFlow

PyTorch

Data visualization

C/C++

Education

Undergraduate or postgraduate degree in Mechanical Engineering, Electrical/Electronic Engineering, Computer Science, AI, Data Science or related field

Tools

Git

Job description

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.

Key Responsibilities

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:

• 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.

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.