Front-End Architectures for Neuromorphic Edge Intelligence
Confirmed on the employer's own hiring board on Oct 18, 2026. First seen by Alion on Oct 31, 2025. HiPEAC scores B on the Alion truth index.
The Center for Industrial Electronics and Multimodal Systems (CEIMM) at Universidad Politécnica de Madrid is reinforcing its research activities in energy-efficient embedded artificial intelligence, with a focus on neuromorphic and reconfigurable computing for intelligent edge devices. Within this context, CEIMM offers a PhD position aimed at advancing mixed-signal and digital architectures that enable adaptive, low-power processing inspired by biological systems. The selected candidate will contribute to the design of hardware and firmware for sensor-integrated, event-driven intelligence, supporting real-time perception and decision-making at the edge.
The PhD project will explore hybrid analog-digital architectures that combine the efficiency of mixed-signal front-ends with the flexibility of reconfigurable digital back-ends. Research will involve both circuit-level and system-level co-design, targeting neuromorphic models capable of dynamic adaptation under stringent energy and latency constraints.
Key research challenges include:
- Design of low-noise, low-power analog/mixed-signal front-ends for multi-modal sensing.
- Signal encoding and sparse-activation strategies for event-based neuromorphic processing.
- Development of reconfigurable digital architectures and firmware enabling runtime adaptation.
- Hardware/software co-design for hybrid AI models with dynamic inference complexity.
- Energy-performance optimization and experimental validation in embedded scenarios.
The selected candidate will be part of a highly international and enthusiastic team. These positions will be funded within the scope of different private and public-funded projects (European and Spanish). The 3-year PhD contract includes health insurance coverage and a gross salary of 25933€. Expenses for attending conferences, summer schools, and workshops will also be covered.
BASIC QUALIFICATIONS: Master’s degree in Electrical /Electronics / Computer Engineering, Computer Science, Physics, or similar. Previous research activities in the fields of interest will be highly appreciated.
PREFERRED SKILLS: Very good knowledge of digital hardware design and SystemVerilog/VHDL; High-level synthesis tools for FPGAs; C/C++ programming for embedded systems. Experience with RISC-V processors is also valuable. A high level of English is required; Spanish is optional.
POSITION AVAILABLE: The selection procedure will remain open until the position is covered. The starting date is flexible, but we prefer it to be ASAP.
INFORMATION: If you are interested in this position and want to have more details about it, please contact Dr. José Miranda Calero ([email protected]) and Dr. Andrés Otero ([email protected]), including the reference [PhD_Neuromorphic] in the subject of your mail. For the application, the following documents will be required:
- CV
- Academic transcript of courses followed and grades obtained provided by your institution.
- Brief letter describing your motivation and previous experience.
About
Universidad Politécnica de Madrid (UPM)
Also known as: UPM
The Technical University of Madrid (UPM) is Spain's largest technical university, offering diverse programs, fostering international collaborations, and excelling in research and innovation across multiple disciplines.
Metadata
Application areas: Healthcare
Topics: Accelerators, ASIC, Bioinformatics, Deep learning, Edge computing, FPGAs, Hardware, IoT, Machine learning, Neural networks, Neuromorphic computing, RISC-V
Summary
The CEIMM at UPM seeks a PhD candidate to research energy-efficient neuromorphic architectures for edge devices. Candidates should have a relevant master’s degree and skills in digital hardware design and programming.