PhD in Hybrid Efficient Convolutional Neural Networks for Lightweight Aerial Object Detection at Universiti Sains Malaysia

The School of Aerospace Engineering at Universiti Sains Malaysia (USM) is offering a PhD opportunity for a Graduate Research Assistant (GRA) to join a high-impact, FRGS-funded research project. The project, titled "Formulation of Hybrid Efficient Convolutional Neural Networks for Lightweight Aerial Object Detection on Embedded Devices," aims to advance research in intelligent algorithms, deep learning, and expert systems, with applications in aerial object detection using embedded devices. This position is ideal for highly motivated candidates with a strong background in Electronics, Mechatronics, Mechanical, Aerospace Engineering, Computer Science, Artificial Intelligence, Robotics, or related fields. Applicants should have programming experience in C/C++, MATLAB, or Python, and must be proficient in English. The role requires a strong research interest and the ability to work independently. The successful candidate will receive a monthly stipend of up to RM2,800 for 36 months, with access to research equipment, materials, and workspace. Additional benefits include opportunities to attend conferences, participate in training programs, and present research findings. The position offers immediate intake, providing an excellent opportunity to contribute to cutting-edge research in convolutional neural networks, aerial object detection, and embedded systems within a leading Malaysian institution. To apply, candidates should submit their CV to Dr. Mohamad Haniff Junos at [email protected]. For further information or inquiries, applicants may contact Dr. Junos via email or WhatsApp. This opportunity is particularly suited for those interested in deep learning, intelligent systems, and aerospace applications.