Deskripsi Pekerjaan
Nanyang Technological University (NTU) is a leading research university renowned for its cutting-edge scientific research and innovation. We are seeking a talented and motivated Research Associate or Research Fellow to join our pioneering indoor farming research team, dedicated to developing AI-powered plant phenotyping tools.
In this role, you will work at the intersection of plant biology and bioinformatics, leveraging advanced technologies to revolutionize indoor agriculture. Your work will directly contribute to sustainable food production systems by applying machine learning and computer vision techniques to analyze plant traits and optimize growth conditions. You will collaborate with interdisciplinary teams of engineers, computer scientists, and biologists to integrate phenotyping tools into automated indoor farming systems, manage large datasets, and publish your findings in top-tier journals. This is an exciting opportunity to contribute to the future of sustainable agriculture while working at one of Asia's premier research institutions.
Tanggung Jawab
- Design and conduct experiments on indoor crops, collecting phenotypic data under various environmental conditions.
- Develop and apply AI and machine learning models for plant phenotyping, including image analysis and data interpretation.
- Collaborate with interdisciplinary teams to integrate phenotyping tools into automated indoor farming systems.
- Manage and analyze large datasets related to plant growth, gene expression, and environmental parameters.
- Publish research findings in peer-reviewed journals and present at international conferences.
- Mentor graduate students and contribute to grant writing efforts.
- Ensure compliance with safety protocols and maintain laboratory equipment.
Kualifikasi
- Master's or PhD degree in Plant Biology, Bioinformatics, Computer Science, or a related field.
- Strong background in plant physiology, genetics, or molecular biology.
- Experience with AI/ML tools and programming languages such as Python, R, or TensorFlow.
- Experience in image analysis, computer vision, or high-throughput phenotyping.
- Excellent analytical and problem-solving skills.
- Strong communication and teamwork abilities.
- Publications in peer-reviewed journals are advantageous.