الملخص
تبحث United Arab Emirates University عن زميل ما بعد الدكتوراه للمشاركة في مشروع متعدد التخصصات لتحسين الاستقرار الحراري وأداء خلايا البيروفسكايت الشمسية. تشمل المهام تصنيع الخلايا واختبارها، وتحضير مواد تغيير الطور وتوصيفها، وتطوير نماذج تعلم آلي للتنبؤ بالأداء وتحسين التصميم. كما يتولى الزميل تحليل البيانات التجريبية وإعداد المنشورات وتقارير المشروع، والتعاون مع فريق البحث والمساهمة في إرشاد الطلبة. يشترط الحصول على دكتوراه في تخصص ذي صلة، وخبرة في الأنظمة الحرارية أو الطاقة الشمسية أو مواد تغيير الطور، وإتقان أدوات الذكاء الاصطناعي مثل Python أو MATLAB أو TensorFlow.
نص الإعلان
كما نُشر على uaeu.ac.ae. نقلناه من موقع صاحب العمل ونعرضه بنصّه الأصلي.
Job description
The Postdoctoral Research Fellow will contribute to an interdisciplinary research project focused on enhancing the thermal stability and performance of perovskite solar cells (PSCs) using nano-enhanced phase change materials (Ne-PCMs) and AI-driven predictive modeling. The role involves designing and fabricating PSC devices, synthesizing and characterizing advanced PCM/Ne-PCM materials, and integrating these systems for thermal management under harsh environmental conditions. The fellow will conduct experimental testing (thermal, electrical, and durability), analyze thermophysical properties, and generate high-quality datasets. In parallel, they will develop and apply machine learning models (e.g., neural networks, random forest, optimization algorithms) to predict system performance and optimize material and design parameters. The position also includes preparing publications, supporting project reporting, collaborating with the research team, and assisting in mentoring students, thereby contributing to the successful execution and dissemination of the project outcomes
Minimum qualification
- PhD in Mechanical Engineering, Materials Science, Energy Engineering, Nanotechnology, or related fields.
- Strong background in thermal systems, solar energy, or phase change materials.
- Experience with nanomaterials synthesis and characterization techniques.
- Knowledge of perovskite solar cells or photovoltaic systems is highly desirable.
- Proficiency in machine learning / AI tools (Python, MATLAB, TensorFlow, etc.).
- Demonstrated record of peer-reviewed publications.
Preferred qualification
- Experience in integrating experimental and computational research.
- Familiarity with thermal modeling, heat transfer, and energy systems.
- Ability to work in multidisciplinary teams (materials + AI + energy).
- Strong scientific writing and communication skills.
Special instructions to applicants
Submit a detailed CV, a statement of research experience, and a list of publications.
Department
Mechanical & Aerospace Eng.-(COE)
College or division
College of Engineering - (COE)