PhD Opportunity ? | Trustworthy Framework for Lightweight AI-Assisted Signal Processing (TinyML/DL)

Are you passionate about the intersection of Artificial Intelligence and the future of telecommunications? ? We are seeking a highly motivated individual to join our research team and pursue a PhD within the Doctoral Program in Information and Communications Technologies in Mobile Networks ?.

The project, titled "Trustworthy Framework for Lightweight AI-Assisted Signal Processing: From Generative Data to Zero-Shot Physical Layer Modules", will be co-directed by Dr.

Eneko Iradier

Gil and Dr.

Iñigo Bilbao

Barrenechea. You will join a cutting-edge, collaborative scientific environment to establish a rigorous, reliable, and software-driven framework for next-generation TinyML wireless communication systems, and to pioneer trustworthy algorithmic solutions (Generative AI, Zero/Few-Shot Learning, Knowledge Distillation) for core physical-layer modules. ?️

? Responsibilities

? Research and establish trustworthy software frameworks for next-generation TinyML physical layer modules.

? Design advanced generative AI models (Diffusion Models, Time-Series GANs) to simulate realistic RF environments and generate complex synthetic data/digital twins.

⚙️ Develop lightweight physical layer processing modules leveraging Zero-Shot and Few-Shot Learning for fast adaptation to unseen environments with high reliability.





? Formulate advanced Knowledge Distillation strategies, specialized complexity-aware loss functions, and structural pruning/quantization for deep model compression.

? Optimize the mathematical trade-off between performance accuracy, trust/generalization bounds, memory footprint, and theoretical computational cost (FLOPs).

? Evaluate and benchmark algorithmic performance across highly dynamic communication scenarios and resource-constrained paradigms.

? Write and communicate scientific advancements in top-tier international journals and leading academic conferences.

? Requirements

? Academic Background: Hold, or be in a position to obtain, a Master’s degree in Telecommunications Engineering, Computer Science, Electronics, Applied Mathematics, or an equivalent discipline.

? Technical Knowledge: Strong motivation for wireless communication systems, physical layer processing, and mathematical optimization.

? Valued Skills: Passion for research, solid programming skills (Python, PyTorch/TensorFlow, MATLAB), familiarity with machine learning principles (Generative AI, Deep Learning), and a good level of English for scientific writing.

? Personal Qualities: Ability to work in a team, proactivity, scientific curiosity, critical thinking, and strong skills for communicating academic results.

📌 PhD Candidate at EHU (Bilbao)
🏢 EHU
📍 Bilbao