The SPEAR centre Research Programme: Fully Funded PhD Opportunities in Integrated PhotonicsAtlantic Technological University (ATU), Letterkenny CampusIn partnership with Ulster University, Tyndall National Institute, and Seagate TechnologyDuration:4 years (Full-time)Expected Start Date: February 2026Location:WiSAR Lab, ATU,Letterkenny, Co. Donegal, IrelandSPEAR Project Background and DescriptionThe Semiconductor and Photonics Education and Research (SPEAR) Centre is a €8.5 million cross-border project which will provide ATU and UU access to an all-island network of research groups and industry partners with the strategic support of Tyndall, and with advisory support from Seagate Technology. The SPEAR Centre is a Photonics research, training and innovation response to challenges outlined in the EU Chips Act 2023 and to simultaneously address existing deficits in high-skill/high-value employment and research infrastructure in the border region.The SPEAR Centre is designed to build research capacity in integrated photonics and semiconductor technologies, while developing Ireland's and Northern Ireland's deep-tech innovation ecosystem. It aims to train the next generation of scientists and engineers to support growth in sectors such as healthcare, telecommunications, advanced manufacturing, and sensor networks.Key to this project will be doctoral training initiative consisting of 15 PhD students delivered in collaboration with Ulster University, Tyndall National Institute, and Seagate Technology, one of the global leaders in data storage and photonics innovation.Four PhD students will be based at ATU Donegal and will join the collaborative Doctoral College with PHD students based in Ulster University and Tyndall National Institute. This will involve co-supervised research, joint training activities, summer schools, industry engagement, and access to advanced infrastructure. These fully funded PhDs provide the opportunity to conduct high-impact applied research while building valuable professional skills across academia and industry.PhD Project DescriptionProject Title: Photonic-Inspired Federated Learning for Communication-Efficient Next Generation Radio Access Networks (NG-RANs)This PhD project will develop a novel, communication-efficient Federated Learning (FL) framework for Next Generation Radio Access Networks (NG-RANs) by drawing inspiration from photonic and neuromorphic computing principles. Instead of frequent, data-heavy model updates, the proposed approach will use event-driven and sparse-update mechanisms so that learning updates are transmitted only when meaningful local changes occur. This will significantly reduce network congestion, lower latency, and enhance privacy.The research will explore hierarchical learning across different network levels (user devices, radio units, distributed units, and central units), while addressing challenges such as network heterogeneity, limited edge resources, and security vulnerabilities. The outcome will be a scalable, privacy-preserving, and high-performance learning framework suitable for future 6G and intelligent edge networks, contributing to advances in telecommunications, IoT systems, and autonomous wireless infrastructure.Candidate RequirementsApplications are invited from graduates who meet the following:Hold a first-class or upper second-class honours degree (or international equivalent) in:o Electronic Engineering/Electrical Engineeringo Photonics / Optical Engineeringo Telecommunications Engineeringo Data Science / Artificial Intelligenceo Computer Engineeringo Applied Computingo Computer Scienceo Or a closely related disciplineEquipped with advanced scientific and engineering research skills to tackle the challenges of developing innovative photonic-inspired computing and communication technologies for next-generation networks, combined with the entrepreneurial, leadership, and teamwork abilities to excel in interdisciplinary academic and industry environments.Demonstrated ability to:o Write technical reports and prepare scientific publicationso Deliver presentations to diverse audienceso Work both independently and collaboratively in a research teamo Manage time and research tasks effectivelyHighly self-motivated with a clear interest in interdisciplinary and applied researchFluency in English is essential. Candidates whose first language is not English must meet ATU's minimum English language requirements (e.g. IELTS 6.0 overall, with no component below 5.5 or equivalent)Desirable Skills and ExperienceStrong programming proficiency in PythonExperience with deep learning frameworks such as PyTorch and/or TensorFlowExperience using data science libraries (e.g. NumPy, Pandas, SciPy, scikit-learn)This PhD position offers:Full coverage of EU/UK academic feesTax-free stipend of €25,000 per annum for four yearsProject-related research expenses and travel supportThese positions are funded by PEACEPLUS, managed by the Special EU Programmes Body (SEUPB).Application ProcedureInterested applicants should submit their application as a single PDF document to: Subject line: SPEAR PhD Application – Your NameThe PDF should include:A one-page cover letter indicating your preferred research theme and your motivationA CV (maximum 2 pages)Academic transcriptsContact details for two academic refereesApplication Deadline:9th January 2026. Early application is strongly recommended.Informal Enquiries: Dr Shagufta Henna – ATU is committed to supporting equality, diversity, and inclusion across all research activities.