Location: 3 Temasek Ave
Work Hours: Monday to Friday, 8:00 am to 5:30 pm
Job Description:
- Cutting-edge Technology Utilization: Harness the power of advanced technologies like machine learning, deep learning, statistics, and operational research to drive innovation and streamline processes in smart manufacturing. Responsibilities include data exploration, model development, and algorithmic decision-making.
- Real-world Application Analysis: Apply data analysis techniques to practical scenarios such as industrial inspection, defect classification, predictive maintenance, and parameter optimization. Directly contribute to enhancing operational efficiency and product quality.
- Intellectual Property Creation: Contribute to the development of Intellectual Property (IP) Rights in Singapore by devising innovative solutions and novel methodologies during research and development endeavors.
- Collaborative Networking: Establish and cultivate partnerships with local universities and research institutions to facilitate collaboration, resource integration, and the initiation of impactful projects that advance the frontier of smart manufacturing.
- Technical Communication: Generate comprehensive technical reports and collaborate effectively with internal cross-functional teams to ensure alignment and dissemination of research findings and project outcomes.
- Integration with Production Needs: Understand and address the production requirements and challenges faced by business groups. Seamlessly integrate research and development insights into the production line to drive tangible outcomes and business success.
Preferred Qualifications:
- Research Publication Track Record: Demonstrated experience in publishing research papers within machine learning, deep learning, or data analysis domains, showcasing both theoretical knowledge and practical application expertise.
- Proficiency in Tools and Frameworks: Familiarity with various machine learning and data analysis tools and frameworks such as Scikit-learn, PyTorch, TensorFlow, Keras, and OpenCV, enabling efficient workflow execution and algorithm development.
- Understanding of Distributed Computing: Knowledge of distributed computing concepts and technologies like Spark, Hadoop, and Hive, facilitating processing and analysis of large-scale datasets and complex manufacturing data streams.
- Bonus Experience: Additional experience in manufacturing practice, software development, digital twin simulation, and mechanism modeling is highly advantageous, contributing to a well-rounded skill set for addressing multifaceted challenges in smart manufacturing.
- Relevant Experience: Minimum of 1 year of relevant experience in data science, machine learning, or related fields, demonstrating practical application of skills and competencies in real-world settings.
- Educational Background: Minimum of a Master's degree in Computer Science Engineering or a related field, providing a solid foundation for advanced research and development activities within the smart manufacturing domain.
EA License 22C1383
EA Personnel R22110043
