Apply for the position of Research Assistant (Machine Learning & Wireless Communication) under the NUST-funded project titled “AI-Driven Optimization Techniques for Next-Generation Wireless Communication Systems.”

Duration: 10 Months

Responsibilities:

1. Design, train and deploy lightweight deep learning models for real-time signal processing and channel estimation.
2. Conduct simulations, model development and performance evaluation on conventional and edge computing platforms.
3. Optimize CNN models for quantization and edge deployment (Jetson, Raspberry Pi).
4. Implement and test signal processing and noise modeling frameworks.
5. Prepare detailed project documentation and technical reports.

Qualifications:
The ideal candidate will hold a BS in Computer Science, Software Engineering, or a related discipline (with a strong background in ML/DL) or MS in Computer Science, Computer Engineering, Data Science, or AI (with research focus on signal processing, communications, or machine learning).

Preferred Skills:

• Proficiency in Python and deep learning frameworks (TensorFlow / PyTorch / Keras)
• Knowledge of wireless communication systems (5G, SISO/MIMO, channel estimation)
• Experience with MATLAB or Python-based communication simulations
• Familiarity with CNN model design, quantization (FP32, FP16, INT8)
• Understanding of embedded inference deployment (TensorRT, ONNX)
• Strong grasp of data handling, training pipelines, and performance benchmarking (NMSE, latency)

Application Procedure:
Interested candidates are invited to submit their CV (including CGPA, relevant projects, research experience, and skillset) at [email protected] with the subject line “NUST Funded Project – Research Assistant (Satellite 5G CNN)”

Deadline: November 6, 2025