PhD Position in Computer Science / Data Science

University of Stavanger Department of Electrical Engineering and Computer Science


PhD position in Computer Science/Data Science


Job description

The University of Stavanger invites applicants for a Ph.D position in Computer Science and Data Science at the Faculty of Science and Technology, Department of Electrical Engineering and Computer Science. The position is vacant from 1.4.2020.


This is a trainee position that will give promising researchers an opportunity for academic development leading to a doctoral degree.


The appointment is for three years with research duties exclusively, or four years with both research and 25% compulsory duties. This will be clarified in the recruitment process.


It is possible to apply to three of the following projects:


1.    Novel Road Safety Services using 5G-enabled Vehicular Edge Computing

2.    Incentives and reputation mechanisms for decentralized systems 

3.    Fairness for permissioned blockchains

4.    Knowledge graphs for conversational AI


Please mark in your application which projects you wish to work on and your order of preference.


For further information regarding required qualifications and each project, please see below.


Vegg Kjølv Egelands hus

Qualification requirements

We are looking for applicants with a strong academic background who have completed a five-year master degree (3+2) within the dubject area, preferably acquired recently; or possess corresponding qualifications that could provide a basis for successfully completing a doctorate.


To be eligible for admission to the doctoral programmes at the University of Stavanger both the master’s thesis grade and the weighted average grade of your master’s degree must individually be equivalent to or better than a B grade.


Applicants with an education from an institution with a different grade scale than A-F should attach a confirmed conversion scale that shows how the grades can be compared with the Norwegian A-F scale.


Emphasis is also placed on the candidate's:


motivation and potential for research within the field

ability to work independently and in a team, be innovative and creative

ability to work structured and handle a heavy workload

having a good command of both oral and written English

We offer

varied duties in a large, exciting and socially important organisation

an ambitious work community which is developing rapidly. We strive to include employees at all levels in strategic decisions and promote an informal atmosphere with a flat organisational structure

colleague-based guidance programme (NyTi) if teaching is a part of your Ph.D

salary in accordance with the State Salary Scale, 17.515, code 1017, NOK 479.600,- gross per year with salary development according to seniority in the position

automatic membership in the Norwegian Public Service Pension Fund, which provides favourable insurance and retirement benefits

favourable membership terms at a gym and at the SIS sports club at campus

employment with an Inclusive Workplace organisation which is committed to reducing sick leave, increasing the proportion of employees with reduced working capacity, and increasing the number of professionally active seniors

"Hjem-jobb-hjem" discounted public transport to and from work

as an employee in Norway, you will have access to an optimal health service, as well as good pensions, generous maternity/paternity leave, and a competitive salary. Nursery places are guaranteed and reasonably priced

relocation programme in event of moving to Norway, including support and language courses for spouses

Other information

See "Regulations concerning terms and conditions of employment for the posts of post-doctoral research fellow and research fellow, research assistant and resident" at the University of Stavanger.


The appointee will be based at the University of Stavanger, with the exception of a stay abroad at a relevant centre of research.


It is a prerequisite that the appointee has a residence which enables him or her to be present at/available to the academic community during ordinary working hours.


The University currently employs few female research fellows within this academic field, and women are therefore particularly encouraged to apply.


The position has been announced in both Norwegian and English. In the case of differences of meaning between the texts, the Norwegian text takes precedence.


Contact information

More information on the position can be obtained from Head of Department Tom Ryen, tel: +47 5183 2029, e-mail:


Information about the appointment procedure can be obtained from HR-advisor Janne Halseth, tel: +47 5183 3525, e-mail:



To apply for this position please follow the link "Apply for this job". Register your application and CV including relevant education and work experience. In your application letter you must show your research interests and motivation to apply for the position.


The following documents must be uploaded as attachments to your application in separate files:




list of publications

other documentation that you consider relevant

The documentation must be available in either a Scandinavian language or in English. If the total size of the attachments exceeds 30 MB, they must be compressed before upload. Information and documentation to be taken into account in the assessment must be submitted within the application dealine.


Please note that information on applicants may be published even if the applicant has requested not to be included in the official list of applicants - see Section 25 of the Freedom of Information Act.


UiS only considers applications and attachments registered in JobbNorge.


Project description and contact persons

1.    Novel Road Safety Services using 5G-enabled Vehicular Edge Computing


Recent revolutionary advances in areas of Internet-of-Things (IoT), Cooperative Intelligent Transport Systems (C-ITS), and 5th generation cellular technology (5G) has provided new opportunities for introducing novel safety services in the road systems. These services will involve the vehicles, road users, road infrastructure and the cloud-based backend and can also significantly benefit from the communication amongst them, represented broadly with vehicle-to-everything (V2X) communication paradigm. It is therefore expected that 5G V2X communication (initially defined in 3GPP Release 14) to play a very crucial role in the formation of future intelligent automotive services including road safety services. In addition to offering several orders of magnitude higher network capacity and bandwidth with mMTC and eMBB (in comparison to LTE), 5G reduces the latency to 1ms in its Ultra-Reliable Low Latency (URLLC) service category, making it a suitable enabling technology for deploying bandwidth-hungry & latency-sensitive applications (e.g., Virtual or Augmented Reality) as well as Mission Critical Communication (MCC) for vehicular safety.


Further, 5G’s native architecture allows for leveraging Multi-access Edge Computing (MEC) solutions in order to reduce the end-to-end communication and computation latency, reducing the traffic load on the network core and taking advantage of higher bandwidths, storage capacity or processing power that are available at the network edge. When used in the context of vehicular networks, MEC can form as a basis for Vehicular Edge Computing (VEC) where among other things, safety services can be hosted. Such safety services can be realized in VEC using a combination of 5G V2X communication techniques, virtualization/softwarization techniques on 5G MEC, and the cloud core back-end system to have a holistic view of the entire road system.                      


The successful candidate will undertake the architectural design and hands-on development of candid services for vehicular and road safety using state-of-the-art 5G mobile technology. A special focus will be given to the safety scenarios within the road tunnels. This will inherently involve the following:


Communication: leveraging the use of 5G/LTE D2D communication using PC5 (sidelink) interface in a software-defined radio (SDR) environment.


VEC server: design and development of VEC platforms for hosting safety applications using latest NFV and SDN techniques.


Safety application: design, development and real-life evaluation of candid vehicular and road safety applications that leverage the use of VEC and V2X communication


Knowledge of communication networking is required, and research track on or experience with design and testing of 4G (LTE), MEC, 5G RAN, SDN, SDR, virtualization techniques/software are desired. Familiarity with 3GPP, ETSI and IETF standards is a plus.


Supervisors: Associate Professor Naeem Khademi (UiS),, and Professor Yan Zhang (UiO)


2.    Incentives and reputation mechanisms for decentralized systems 


Decentralized systems are mainly rooted in distributed systems, particularly, p2p systems and recently on blockchain and other distributed ledger technologies. They offer opportunities and research challenges regarding computational infrastructure, communication, storage as well as the design of governance frameworks that sustain decentralized systems. In some cases, addressing these challenges will require to reconsider or revive p2p systems research under the current socio-technical perspectives.


Crypto-assets, aka cryptocurrencies and tokens, can provide economic incentives to service providers in decentralized systems. Due to the diversity of decentralized systems, mechanisms that allow multi crypto-assets facilitate interoperability. Crypto-assets do not require trusted intermediaries for storage and electronic exchange. Crypto-assets did not reach global acceptance yet, however many cities are growing the number of merchants and ATM that accept bitcoin or other coins. Individuals and businesses from countries that are suffering economic uncertainties are adopting crypto-assets such bitcoin to counteract high inflation (some examples are Argentina, Venezuela, etc.).


On the other side, consumers in decentralized systems require some type of reputation mechanism to choose among service providers. Whom should they trust? Cultural differences mark important distinctions among communities, and impact on how people decide to whom they trust for making business. Trust is multidimensional. Bonds that are built based on cognitive trust are based on experiences in a task-driven society/community. Bonds that are built based on affective trust are based on experiences in a relationship-driven society/community. We will consider both dimensions and their interactions.


The purpose of this project is to evaluate existing and novel incentives and reputation models and build those mechanisms in decentralized systems. Applicants should have a good understanding and experience building distributed systems. Additional experience with game-theory, economics, and/or simulations is welcome.


Supervisors: Associate Professor Vero Estrada-Galiñanes,, and Professor Hein Meling.


3.    Fairness for permissioned blockchains


Blockchain and distributed ledger technology allows to create a trusted platform among multiple agents with unknown or even conflicting goals. Application scenarios range from financial technology to decentralized markets, document verification, and IoT.


In this project we want to focus on permissioned blockchain systems, that can be run among known or authenticated agents, and allow to avoid the wasteful resource usage of proof of work consensus. Building on byzantine fault tolerance, these systems can provide reasonable performance and tolerate arbitrary failures by some of the participants. However, the deployment of such systems still has a significant cost impeding adoption in IoT and fog based applications. Further, the fault-tolerant design of such systems allows free riding which may become a significant problem when running on IoT or fog devices.


In this project, we aim to design and evaluate novel algorithms for permissioned blockchain systems that improve scalability and reduce free-riding by ensuring that all participants receive a fair compensation or utility for the provided bandwidth and computational resources.


Besides fairness and scalability, also other concerns related to the security and performance of blockchain systems are relevant for this project.


Supervisors: Associate Professor Leander Jehl,, and Professor Hein Meling.


4.    Knowledge graphs for conversational AI


Knowledge graphs, organizing structured information about entities, and their attributes and relationships, are ubiquitous today. They have become powerful assets for a broad range of search, recommendation, and mining scenarios. Examples include enabling rich knowledge panels and direct answers in search result pages, supporting data exploration and visualization, and facilitating media monitoring and reputation management. This project focuses on the usage of knowledge graphs for conversational AI, in particular, for conversational search and recommendation tasks.


The recent success of deep learning techniques in different areas of natural language processing has enabled conversational AI systems to generate human-like responses. These systems, however, still have from little to no understanding of the actual meaning of the dialog. Knowledge graphs are needed to make human-machine interactions more grounded in knowledge. Knowledge graphs may also be utilized for personalized experiences.


This project involves various tasks around knowledge graphs for conversational information access, including the development of (i) models of interaction, (ii) algorithms for personalized search and recommendation, (iii) methods for multi-modal result presentation, and (iv) evaluation methodology of resources.


The candidate is expected to have a background in information retrieval, natural language processing, or machine learning.


Supervisor: Professor Krisztian Balog,


Campus flyfoto

UiS - challenge the well-known and explore the unknown

The University of Stavanger (UiS) has about 12,000 students and 1,700 employees. We are the only Norwegian member of the European Consortium of Innovative Universities. The university has high ambitions. We will have an innovative and international profile, and will be a driving force in knowledge development and in the process of societal change. Together with our staff and students, we will challenge the well-known and explore the unknown.


Department of Electrical Engineering and Computer Science is part of the Faculty of Science and Technology.


The department carries out research within computer science, data Science, cybernetics and signal processing, and offers bachelor programs in electrica engineering and computer science, master programs in computer science, data science and cybernetics/signal processing, and a PhD program in information technology. There are currently 50 employees, including research fellows and postdocs, and 600 students at the department.

In your application, please refer to