Company Description

The University of Ljubljana, established in 1919, is the oldest and largest higher education and research institution in Slovenia, ranked among the top 3% of universities worldwide. With 23 faculties and three academies of art, the University offers diverse programs in fields such as natural sciences, engineering, social sciences, humanities, medicine, and arts. Supporting over 38,500 students and 5,800 staff members, it collaborates with top global universities. The University fosters professional connections through its Alumni Relations, enhances student career readiness via its Career Centers, and promotes innovation through its Knowledge Transfer Office.

Role Description

Young researchers are doctoral students working in UL member institutions in research programmes. Their doctoral tuition fees are fully covered, and their employer provides them with the material resources they need to carry out their research.

The young researcher will work at the intersection of Things-to-Cloud computing, Distributed Ledger Technologies, and Artificial Intelligence. This research field is of high strategic relevance due to the accelerated digital transformation of industry and public services, the widespread deployment of Internet of Things infrastructures, and the growing demand for cross border and federated AI solutions operating across heterogeneous computing environments. Contemporary use cases in domains such as smart infrastructure, mobility, energy systems, and digital public services are characterised by uncertainty, dynamic resource availability, evolving regulatory frameworks, and partially observable system states. These conditions necessitate robust and adaptive architectures capable of operating reliably across the compute continuum while ensuring trust, accountability, privacy, and regulatory compliance. The research domain therefore focuses on the design of trustworthy and scalable AI architectures that support decentralised decision making and governance in complex multi stakeholder ecosystems.

The primary research goal will be the development of solutions that extend beyond conventional federated learning and enable scalable AI data processing across heterogeneous infrastructures and jurisdictions. The work will address the coordinated development, deployment, and operation of AI workflows across edge, cloud, and high performance computing environments, with explicit attention to interoperability, performance, privacy, and trustworthiness. Given the inherent uncertainty in distributed environments and real world use cases, the research will incorporate stochastic methods for decision making and prediction, including probabilistic reasoning, uncertainty quantification, and adaptive resource allocation strategies. In parallel, the research will develop novel approaches to enhance data availability, quality, and consistency in decentralised AI systems, including mitigation of dataset imbalance, optimisation of data transfer volumes, and robust distributed data management mechanisms.

The researcher is expected to demonstrate strong analytical capability and the ability to independently address complex research challenges in distributed systems and artificial intelligence. 

Qualifications

• Master’s degree in computer science, electrical engineering, or a related discipline.
• Strong programming skills and experience with modern software development tools.
• Strong organizational and problem-solving skills, attention to detail, and the capacity to manage multiple tasks efficiently.
• Good ability for professional communication and teamwork.
• Good proficiency in the English language.
• Ability to collaborate within multidisciplinary teams and effectively communicate research ideas.