Job Description
Prof. Mohamed Hamouda’s Integrated Water Cycle Lab invites applications for a research associate starting September 2026 to work on a research project in the area of Remote Sensing of Water Quality. The role focuses on:
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Processing and analysis of multi-sensor satellite data (e.g., MODIS, Sentinel, Landsat, PRISMA)
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Integration of remote sensing and in-situ datasets
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Development and implementation of machine learning and physics-informed models
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Assisting in model validation, visualization, and development of early warning tools
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Preparing technical reports, journal publications, and project documentation
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Coordinating with research partners and supporting field campaigns
Minimum Qualification
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Master’s degree in Environmental Engineering, Civil Engineering, Remote Sensing, Data Science, or a related field (PhD preferred)
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Minimum 1–3 years of research or industry experience in a relevant field
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Experience in remote sensing data processing and GIS
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Strong programming skills in Python, MATLAB, or R
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Experience with machine learning techniques and data analysis
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Strong technical writing and communication skills
Preferred Qualification
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Experience with water quality modeling or oceanographic data
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Familiarity with satellite platforms (MODIS, Sentinel, Landsat, hyperspectral data)
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Experience with deep learning frameworks (e.g., TensorFlow, PyTorch)
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Knowledge of physics-informed machine learning or environmental modeling
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Experience working on projects in arid or coastal environments (UAE/Gulf region preferred)
Special Instructions to Applicant
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Detailed CV
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Cover letter outlining research experience
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Copies of academic transcripts
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Contact details of at least two referees
Close Date Kindly apply
before
the closing date.
01/07/2026
Apply
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