Harun Siljak

Professor at Trinity College Dublin

Trinity College Dublin
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Ireland

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Positions (1)

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Nicola Marchetti

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Trinity College Dublin

PhD Position: Topology in Distributed Quantum Networks (QUESTING Project) at Trinity College Dublin

Trinity College Dublin, Ireland’s leading university, invites applications for a PhD position in the field of distributed quantum networks as part of the Marie Skłodowska-Curie Action project ‘QUESTING’. Ranked 75th globally (QS World University Rankings 2026), Trinity offers a vibrant research environment steeped in history and innovation. The successful candidate will join the Wireless Engineering and Complexity Science Lab (WhyCOM) and Not A Space Race Lab (NASR), working under the supervision of Professor Nicola Marchetti and Professor Harun Siljak. This PhD project focuses on investigating the influence of topology in the design and operation of distributed quantum networks. As part of the QUESTING Doctoral Network, you will be immersed in a pioneering initiative that integrates mathematics, physics, computing, and communications engineering with sociocultural and ethical perspectives. The program aims to cultivate a new generation of 'Q-System Innovators' equipped to address critical gaps in quantum technology through interdisciplinary education and training. QUESTING’s holistic methodology spans theoretical advancements and real-world applications, including secure quantum communication, distributed resource management, and sustainable network topologies. The project emphasizes participatory research, co-design processes, and industry-academic collaboration, ensuring alignment with global challenges such as cybersecurity, digital transformation, and equitable access to emerging technologies. This initiative supports the European Union's Quantum Technologies Flagship and the UN Sustainable Development Goals, fostering innovation-driven growth and preparing Europe for leadership in the quantum revolution. Funding for this position is provided through the Marie Skłodowska-Curie Action Doctoral Network, typically covering tuition and a competitive stipend. Trinity College Dublin is committed to equality, diversity, and inclusion, welcoming applicants from all backgrounds, including those with disabilities, non-traditional career paths, or those displaced due to war. The university is recognized as an EU Sustainable Gender Equality Champion and holds an Athena Swan Silver award for its ongoing work in advancing gender equality. Eligibility & Requirements: Applicants should possess a strong undergraduate or master’s degree in physics, computer science, mathematics, electrical engineering, or a closely related discipline. Experience or interest in quantum networks, distributed systems, or network topology is highly desirable. Candidates must demonstrate academic excellence, motivation for interdisciplinary research, and proficiency in English. International applicants and those from diverse backgrounds are encouraged to apply. Application Process: Submit a cover letter, CV, academic transcripts, and contact details for two referees (including email addresses) in a single PDF file to Professor Nicola Marchetti and Prof Harun Siljak via the provided email addresses. Only shortlisted applicants will be contacted for an interview with the supervisors and their teams. The application deadline is July 31, 2026. For further details and to apply, visit the official application link. Trinity College Dublin offers a supportive, family-friendly working environment and is committed to work-life balance for all staff and students.

2 months ago

Articles (1)

A Hybrid Indoor Altimetry Based on Barometer and UWB

Accurate altimetry is essential for location-based services in commercial and industrial applications. However, current altimetry methods only provide low-accuracy measurements, particularly in multistorey buildings with irregular structures, such as hollow areas found in various industrial and commercial sites. This paper innovatively proposes a tightly coupled indoor altimetry system that utilizes floor identification to improve height measurement accuracy. The system includes two optimized algorithms that improve floor identification accuracy through activity detection and address the problem of difficult convergence of z-axis coordinates due to indoor coplanarity by applying constraints to iterative least squares (ILS). Two experiments were conducted in a teaching building and a laboratory, including an irregular environment with a hollow area. The results show that our proposed method for identifying floors based on activity detection outperforms other methods. In dynamic experiments, our method effectively eliminates repeated transformations during the up- and downstairs process, and in static experiments, it minimizes the impact of barometric drift. Furthermore, our proposed altimetry method based on constrained ILS achieves significantly improved positioning accuracy compared to ILS, 1D-CNN, and WC. Specifically, in the teaching building, our method achieves improvements of 0.84 m, 0.288 m, and 0.248 m, respectively, while in the laboratory, the improvements are 2.607 m, 0.696 m, and 0.625 m.

Year:

2023

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