Research Assistant - Smart Aqua-PV Systems And Monitoring

Job Description

The Department of Mechanical and Aerospace Engineering at the United Arab Emirates University invites applications for a full-time Research Assistant under the 24-month A-TRIP project "Smart Aqua-PV: A Solar-Powered Digital Twin and AI-Driven Smart Aquaculture Pilot for Sustainable Protein Production in Arid Environments," conducted in collaboration with the Massachusetts Institute of Technology (MIT). The Research Assistant will support the installation, operation, and experimental validation of a solar-powered recirculating aquaculture system; deployment, calibration, and maintenance of water-quality, environmental, IoT, and piezo-acoustic sensors; continuous data logging and quality control; monitoring of fish health, feeding, RAS performance, PV generation, battery status, and system uptime; controlled stress tests; preliminary Python/MATLAB analysis and dashboard/digital-twin support; and preparation of technical reports, publications, manuals, and stakeholder workshops. Regular on-site work at UAEU research facilities is required.

Minimum Qualification

• Master's degree in Mechanical, Electrical, Computer, Environmental, Agricultural/Aquaculture Engineering, or a closely related field.
• Hands-on experience with experimental systems, sensors, instrumentation, data acquisition, IoT, or control.
• Working knowledge of Python, MATLAB, or comparable data-analysis tools.
• Strong data-management, technical writing, and communication skills.
• Ability to work independently, safely, and collaboratively in laboratory and field settings.
  
  

Preferred Qualification

• Experience with recirculating aquaculture systems, aquaponics, water-quality monitoring, or fish-production systems.
• Experience with solar PV, batteries, pumps, aeration, renewable-energy systems, or energy management.
• Familiarity with Arduino, ESP32, Raspberry Pi, cloud dashboards, databases, or wireless sensor networks.
• Exposure to machine learning, time-series prediction, anomaly detection, or digital-twin modeling.
• Peer-reviewed publications or experience supporting multidisciplinary research projects.
  
  

Special Instructions to Applicant

Submit a detailed CV, cover letter, copies of degree certificates/transcripts, and contact details for two referees.

Close Date Kindly apply before the closing date.

10/09/2026

Apply

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