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Research Assistant - Smart Aqua-PV Systems and Monitoring

Job in Al Ain, UAE/Dubai
Listing for: United Arab Emirates University
Full Time position
Listed on 2026-08-30
Job specializations:
  • Engineering
    Electrical Engineering
  • Research/Development
    Data Scientist
Salary/Wage Range or Industry Benchmark: 120000 - 180000 AED Yearly AED 120000.00 180000.00 YEAR
Job Description & How to Apply Below

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 Qualifications:
  • 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 Qualifications:
  • 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, ESP
    32, 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.
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