Exploring Research Opportunities at SIT: A Gateway to Innovation

At the Singapore Institute of Technology (SIT), the emphasis on bridging academia and industry is evident in its approach to applied research. As a University of Applied Learning, SIT recognizes that the demands of the industry are constantly evolving. By closely collaborating with various sectors, SIT not only enhances its research initiatives but also equips its research staff with relevant skill sets in applied research. This synergy creates a unique environment where academic knowledge meets real-world application.

The Role of a Research Engineer

One of the key positions available within this innovative ecosystem is that of a Research Engineer. Tasked with supporting and contributing to industry innovation research projects, this role is critical in developing cutting-edge technologies, especially within the realm of deep learning and computer vision. The Research Engineer works closely with the Principal Investigator (PI), Co-PI, and fellow team members, immersing themselves in a collaborative environment dedicated to advancing technological frontiers.

Key Responsibilities

The responsibilities of a Research Engineer at SIT are both diverse and challenging. As a participant in the research project, the engineer actively engages in managing timelines and achieving deliverables alongside the PI and Co-PI. Specific tasks include:

1. Developing Deep Learning Models: A significant part of the role involves creating, training, and optimizing deep learning algorithms for tasks such as object detection, classification, and segmentation. The use of real-world datasets is a cornerstone for practical model development.

2. Software Development: The engineer designs and implements software modules to integrate the developed models into a working prototype. Familiarity with programming languages, particularly Python, and libraries like PyQt, OpenCV, and NumPy, is crucial for creating software that interacts seamlessly with deep learning models.

3. Data Annotation: A foundational aspect of machine learning is the annotation of data. The engineer will undertake this task to prepare datasets that are essential for training accurate models.

4. Conducting Experiments: Analyzing results and iterating models to enhance efficiency and accuracy is a continuous process. The engineer must be comfortable experimenting with various approaches to discover the most effective methods.

5. Documentation and Reporting: Technical documentation, project reports, and academic publications are essential for sharing findings and securing future funding. The Research Engineer must be adept at presenting complex information clearly and concisely.

6. Collaboration with Industry Partners: Engaging with industry stakeholders is vital for technology transfer. The engineer contributes to fostering these relationships, ensuring that research findings can be effectively transitioned into practical applications.

Required Skill Set

For those aspiring to become a Research Engineer at SIT, a robust technical background is paramount. Essential qualifications include:

1. Deep Learning Frameworks: Proficient knowledge and hands-on experience with frameworks like PyTorch and TensorFlow are critical. These tools are the backbone of developing machine learning algorithms.

2. Familiarity with Models and Algorithms: Experience with various deep learning models, such as YOLO, U-Net, and ResNet, cannot be overstated. Understanding these models allows the engineer to assess their effectiveness in diverse scenarios.

3. Computer Vision Techniques: A strong foundation in computer vision algorithms is necessary for tackling problems related to image and video processing.

4. Programming Proficiency: Expertise in Python, along with libraries essential for developing Windows desktop applications, is a requirement. This includes a working knowledge of libraries like OpenCV and scikit-learn.

5. Educational Background: A minimum of a Bachelor’s degree in Computer Science, Electrical/Electronic/Software Engineering, or a related field is required. Advanced degrees such as a Master’s or PhD can provide a competitive edge in the application process.

Desired Additional Knowledge

While the core skill set is essential, familiarity with several additional areas can further enhance a candidate’s profile:

• Kaggle Competitions: Participation in data science competitions showcases practical skills in problem-solving and model development.
• Model Deployment: Understanding frameworks that facilitate the deployment of models, such as ONNX and TensorRT, is an added advantage.
• Edge Computing: Knowledge in embedded vision systems, like the NVIDIA Jetson Nano, is increasingly relevant as the industry shifts toward more localized processing.
• Real-Time Processing: Experience with GPU acceleration for real-time applications highlights a candidate’s capability to handle demanding tasks.
• Industry R&D: Previous involvement in research and development projects in industry settings can provide practical insights that are invaluable for the role.

Key Competencies

Equipped with the right technical skills, a Research Engineer at SIT must also embody key competencies to thrive in a research-oriented environment:

• Collaboration Skills: The ability to build and maintain strong relationships with team members and external partners is crucial for successful project execution.
• Self-Motivation: A commitment to continuous learning and development is essential, as the field of artificial intelligence is rapidly evolving.
• Communication Proficiency: Strong technical writing and presentation skills are necessary for effective research reporting and academic publication.
• Analytical Ability: Demonstrating critical thinking and problem-solving skills allows the engineer to navigate complex challenges.
• Initiative: Taking ownership of projects and carrying out tasks independently is encouraged, fostering a sense of responsibility and innovation.

By merging theoretical knowledge with practical applications, SIT presents a rich landscape for researchers eager to make significant contributions to the field of applied research. The role of a Research Engineer is not just a job; it is an opportunity to be part of an exciting journey that promises to shape the future of technology.