Key Responsibilities:
1. Research and Develop AI Solutions including:
- Research, design and implement machine learning algorithms and models to analyze aquaculture data.
- Research and apply computer vision techniques for automated image analysis including image enhancement techniques to optimize result.
- Create predictive models to improve process management and resources optimization.
- Conduct statistical analysis and develop algorithms to provide insights for supporting intelligent decision-making process.
- Evaluate and ensure model accuracy, robustness, and scalability using appropriate evaluation metrics.
- Collaborate with aquaculture experts and technical experts to identify relevant data sources, develop data collection and pipeline strategies.
- Implement data processing (including data cleaning and edge computing), integration and storage solutions to efficiently manage data from various sources, such as sensors, IoT devices, and monitoring systems etc..
2. Data Collection and Management such as:
- Collaborate with aquaculture experts and technical experts to identify relevant data sources, develop data collection and pipeline strategies.
- Implement data processing (including data cleaning and edge computing), integration and storage solutions to efficiently manage data from various sources, such as sensors, IoT devices, and monitoring systems etc..
- 3. Collaborate with software engineers and technical teams to research and develop AI models into aquaculture management solution/workflow.
4. Stay updated with the latest advancements in AI, machine learning, and aquaculture technologies.
5. Contribute to the development of intellectual property, patents, or scientific publications in the field of AI for aquaculture.
Requirement:
- Master's degree in computer science, software engineering, data science/analytics or a related field. A Ph.D. is a plus;
- At least 3 years of working experience in related field. Fresh graduate with Ph.D. degree may be considered;
- Strong background in machine learning, deep learning frameworks, and statistical analysis. Solid understanding of data structures, algorithms, and software design principles;
- Demonstrated expertise in developing and implementing computer vision pipelines, understanding visual data processing, and algorithms is a strong plus. Experience in real-time computer vision application development on edge platform is a strong plus;
- Proficiency in programming languages such as Python, R, or MATLAB, and experience with relevant libraries and frameworks (e.g., OpenCV, Pillow, TensorFlow, PyTorch, scikit-learn);
- Excellent problem-solving and analytical skills, and ability to manage multiple projects and prioritize tasks effectively;
- Strong communication and collaboration abilities to work effectively both in a multidisciplinary team and also independently, to deliver high-quality outcomes;
- Possess personality/characteristics and share values of curiosity, open mindset, can-do and continuous learning attitude, accountability and willingness to take new initiatives, teamwork spirit, integrity, and passion to make a positive impact;
- Comfortable and capacity to work with an initial small team at an entrepreneurial and dynamic setting.
