Deskripsi Pekerjaan
Are you a passionate researcher looking to push the boundaries of 6G technology? The School of Electrical and Electronic Engineering (EEE) at Nanyang Technological University (NTU), Singapore, invites applications for a Research Fellow position focusing on Integrated Sensing and Communications (ISAC) systems powered by Artificial Intelligence.
As a Research Fellow at one of the world's leading engineering schools, you will be at the forefront of the next generation of wireless communication. This role offers an unparalleled opportunity to work on cutting-edge research, collaborating with world-class faculty to bridge the gap between sensing and communication through advanced AI and machine learning architectures. You will lead technical investigations, drive innovation in signal processing, and contribute to high-impact academic publications while tackling real-world deployment challenges.
If you are driven by intellectual curiosity and have a track record in developing robust, scalable solutions in wireless networking or related fields, we want to hear from you.
Tanggung Jawab
- Lead innovative research projects in the domain of AI-driven ISAC systems.
- Design, develop, and implement novel signal processing algorithms for sensing-communication integration.
- Conduct high-level simulations and experimental prototyping to validate research frameworks.
- Author high-quality academic papers for publication in prestigious IEEE journals and top-tier conferences.
- Collaborate with interdisciplinary teams and mentor junior researchers or graduate students.
- Contribute to grant proposals and manage project deliverables within established timelines.
- Present research findings at international workshops and technical seminars.
Kualifikasi
- PhD in Electrical Engineering, Computer Science, or a closely related field from a reputable university.
- Strong background in wireless communications, signal processing, or radar systems.
- Proficiency in programming languages such as Python, MATLAB, or C++.
- Proven experience in machine learning and deep learning frameworks (e.g., PyTorch, TensorFlow).
- Strong publication record in reputable journals and conferences (e.g., IEEE TWC, TSP, TCOM).
- Excellent communication and analytical skills, with a high degree of technical independence.
- Ability to work effectively in a diverse, multinational, and high-performance research environment.