National Water and Energy Center of UAE university is seeking a highly motivated and skilled Post-Doctoral Researcher to join our team on a project aimed at understanding and predicting changes in rainfall patterns due to climate change in the United Arab Emirates (UAE). The selected candidate will play a crucial role in applying advanced computational and machine learning techniques to develop a high-resolution gridded rainfall dataset, evaluate the impacts of climate change on rainfall, and predict extreme rainfall events that may lead to flash floods. This position requires expertise in hydrology, climatology, remote sensing, and machine learning algorithms. Key Responsibilities  Data Analysis and Model Development: Develop and implement deep learning models for bias correction based on satellite rainfall products and Global Climate Models (GCMs). Analyze various satellite rainfall products to select the most appropriate ones for the UAE context.  Dataset Development: Devise a methodology for producing a high-resolution gridded rainfall dataset for the UAE, including the assessment of satellite-based rainfall products and GCMs for accurate rainfall projection.  Performance Evaluation: Conduct thorough performance evaluations of the developed gridded rainfall dataset against ground observations and existing gridded rainfall datasets. Utilize advanced computational techniques for evaluating and improving the spatial and temporal resolution of rainfall data.  Impact Analysis: Examine the impacts of climate change on rainfall patterns in the UAE, utilizing the created dataset to predict extreme rainfall events and assess their potential to trigger flash floods.  Collaboration and Reporting: Work collaboratively with project team members, including principal investigators (PIs) and co-PIs, to ensure the successful completion of the project. Prepare and present findings at conferences and meetings. Contribute to the drafting and publication of research articles in high-impact journals.  Policy and Decision-Making Support: Assist in providing valuable insights to governmental organizations and policymakers for informed decision-making related to water resource management and climate change adaptation measures.

 Ph.D. in Hydrology, Water Resources, Environmental Science, or a related field, with a strong focus on remote sensing and machine learning applications in water-related studies.

 Ph.D. in Hydrology, Water Resources, Environmental Science, or a related field, with a strong focus on remote sensing and machine learning applications in water-related studies.

 Proven experience in machine learning and deep learning techniques, especially as applied to hydrological modeling, rainfall prediction, and bias correction of satellite precipitation products.  Strong programming skills in Python, R, or similar languages, with experience in handling large datasets and using machine learning libraries (e.g., TensorFlow, PyTorch).  Familiarity with satellite rainfall products and Global Climate Models (GCMs), including their application and limitations in hydrological studies.  Excellent analytical skills.  Strong communication skills, both written and verbal, with a proven track record of publishing research findings in peer-reviewed journals and presenting at international conferences.  Ability to work collaboratively in a multidisciplinary team, as well as independently, with strong organizational and project management skills.

30/06/2024