Postdoctoral Researcher – AI & Smart Aquaculture Systems
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Key skills for this role
About the Role
The Department of Mechanical and Aerospace Engineering at UAEU seeks a Postdoctoral Researcher for a 2-year project on AI-driven smart aquaculture. The role involves developing digital twin models, AI algorithms for optimization, and integrating sensor data.
Key Skills for This Role
Responsibilities
- Development of digital twin models integrating solar energy, RAS dynamics, and sensor data
- Design and implementation of AI algorithms for feeding optimization, water quality prediction, and anomaly detection
- Integration of MIT piezo acoustic sensing data into the AI framework
- Simulation of operational scenarios (heat stress, power interruption, system disturbances)
- Data analytics and predictive modeling using machine learning tools
- Supervision of graduate students (PhD and MSc)
- Preparation of high impact journal publications
- Contribution to techno economic analysis and scalability modeling
- Participation in stakeholder workshops and project dissemination
Requirements
- PhD in Mechanical Engineering, Electrical Engineering, Computer Engineering, Energy Systems, AI, or a closely related field
- Strong background in machine learning and data driven modeling
- Experience with Python, MATLAB, or similar computational tools
- Experience in system modeling and simulation
- Proven publication record in peer reviewed journals
- Ability to manage research tasks independently
- Strong scientific writing and communication skills
Full Job Posting
Job Description
- The Department of Mechanical and Aerospace Engineering at the United Arab Emirates University (UAEU) is seeking a highly motivated Postdoctoral Researcher for a 2 year A TRIP funded project titled: “Smart Aqua PV: A Solar Powered Digital Twin and AI Driven Smart Aquaculture Pilot for Sustainable Pro
Responsibilities
- Development of digital twin models integrating solar energy, RAS dynamics, and sensor data
- Design and implementation of AI algorithms for feeding optimization, water quality prediction, and anomaly detection
- Integration of MIT piezo acoustic sensing data into the AI framework
- Simulation of operational scenarios (heat stress, power interruption, system disturbances)
- Data analytics and predictive modeling using machine learning tools
- Supervision of graduate students (PhD and MSc)
- Preparation of high impact journal publications
- Contribution to techno economic analysis and scalability modeling
- Participation in stakeholder workshops and project dissemination
Minimum Qualification
- PhD in Mechanical Engineering, Electrical Engineering, Computer Engineering, Energy Systems, AI, or a closely related field
- Strong background in machine learning and data driven modeling
- Experience with Python, MATLAB, or similar computational tools
- Experience in system modeling and simulation
- Proven publication record in peer reviewed journals
- Ability to manage research tasks independently
- Strong scientific writing and communication skills
Preferred Qualification
- Experience in digital twin modeling
- Experience in IoT data systems or sensor integration
- Background in renewable energy systems or solar PV
- Experience in aquaculture systems or environmental monitoring (advantageous but not mandatory)
- Knowledge of optimization algorithms and agent based models
- Experience in real time control systems
- Experience working on interdisciplinary or international projects
- Willingness to collaborate with MIT research team
Special Instructions to Applicant
- A detailed CV
- Evidence of prior experience in machine learning, system modeling, or energy systems
- PDF copies of 2 representative journal publications
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