Senior Neuromorphic Researcher

Gradiant is seeking exceptional researchers who hold a PhD and are interested in pursuing a research project within its team.

Compruebe a continuación si tiene lo necesario para esta oportunidad y, si es así, envíe su solicitud lo antes posible.

About Gradiant

Gradiant (GRAD) is a private Research and Technology Organization (RTO) based in Vigo, Spain, with strong foundations on telecommunications and related ICT disciplines. GRAD aims to improve the competitiveness of companies through transfer of knowledge in the areas of connectivity, intelligence, and security.

Over the last 17 years, GRAD has developed more than 340 different R&D&I projects, which includes over 45 European projects, becoming one of the main drivers of technological innovation in Galicia (Spain).

In 2011, Gradiant was included in the demanding state registration of Technological Innovation Centres (known in Spanish as CIT). Since 2018, Gradiant has held the Certification in Information Security Management Systems UNE-EN ISO/IEC 27001.

As an advanced R&D center, GRADIANT has expertise in many of the aspects of the state of the art in AI. Specifically, its researchers have published more than 30 contributions in the last 5 years in relevant journals and conferences.

Also, GRADIANT has been an active participant in many international projects, where its main contribution has been the development of state-of-the-art AI systems for several use cases, including but not limited to AI payloads for autonomous aircrafts, AI algorithms deployment in FPGA, AI algorithms applied to manufacturing and multivariate time-series and AI applied to Natural Language Processing.

GRADIANT is an R&D centre organized in three main technical areas, each of them with a clear focus and expertise in a defined technical field. For this FWP, the Intelligent Systems department will be involved:

- The Intelligent Systems area, with strong expertise in Artificial Intelligence, Machine Learning and advanced data analytics, focuses on the design and development of intelligent, data‑driven solutions for complex real‑world problems. Its work covers areas such as multimodal data fusion, perception and decision‑support systems, predictive analytics, and edge–cloud AI architectures, applied to demanding verticals including manufacturing and Industry 4.0, health , agri‑food, aerospace and defence.

- The Advanced Communications area, with expertise in research, design and development of new generation wireless communications systems, with special focus on 5G/6G and satellite technologies, signal intelligence solutions, technologies for autonomous systems (UAVs, UGVs and USVs) and new quantum and photonic technologies, with application mainly in the fields of Telecommunications, Aerospace and Security and Defence.

- The Security and Privacy area, with expertise in cybersecurity, data protection and trusted digital systems, covering the design and development of secure architectures, privacy‑preserving technologies and digital identity solutions. Its activities include protection of critical infrastructures, secure communications, cyber‑threat detection and response, cryptography and post‑quantum security, as well as compliance with security and data‑protection regulations. The area applies these capabilities across multiple sectors, with special relevance in Industry 4.0, Telecommunications, eHealth, Smart Cities, and Security and Defence.

Approximately 90% of GRADIANT staff are Telecommunications Engineers. Of a total of more than 240 highly qualified workers, 27 are in possession of a Ph.D. in technical specialties.

Project Overview

The project’s main objective needs to be aligned with the following key concepts of neuromorphic computing: to conduct research and contribute to the state of the art related to:

- Third generation artificial neural networks: New mathematical and computational models that mimic the function of biological neurons and their interconnection in the brain.

- Synaptic plasticity: The ability of connections between neurons (synapses) to change and continuously adapt based on experience and learning.

- Parallelism and energy efficiency: The human brain is efficient in terms of energy consumption and massive parallel processing capacity. Neurocomputing seeks to replicate this parallelism to perform complex tasks with a fraction of the energy consumption of traditional systems. This is specially interesting for AI-on the edge use cases.

To achieve this, the following technological topics are proposed:

- Review, expansion, and updating of documentation on the state of the art in neuromorphic computing. Analysis of new publications, launches of new hardware devices or software tools relevant to the field of neurocomputing, and contextualization of their relevance to project objectives.

- Research into new architectures of n