PhD Student in Pervasive and Mobile Computing

In the coming years, we see the application of AI in the Nordic region, especially, Sweden, Finland and Norway, to contribute towards a more resilient, inclusive and sustainable healthcare system by improving equitable access to high quality healthcare for people living in remote and sparsely populated areas. This is evident by the multibillion-dollar investments that are made in Norrbotten and Västerbotten in significant projects aimed at a more sustainable society. Luleå University of Technology (LTU) is involved in several of these highly topical research projects and the societal transformation that follows with the development of AI-powered smart care solutions.

The position is at the Department of Computer Science, Electrical and Space Engineering, Division of Computer Science, at Luleå University of Technology (LTU) at Skellefteå Campus – with a focus on AI in healthcare for developing smart care solutions in the Nordic region. You will work within an active research group with close collaboration with other universities in the Nordic region and municipality/industry partners on real use cases for e-health solutions conducting research in software systems, distributed systems, network technologies and advanced data analysis.

The opportunity to do a Ph.D. in a dynamic, international research environment in collaboration with municipalities and industry in the Nordics. Doctoral studies at an institution that is active and supportive in matters such as working conditions, equality, and diversity, as well as study and work environment.

Subject Description

Pervasive and mobile computing address distributed systems and mobile networks which enable mobility, ubiquity, security and interactivity of computers, data, software, and users.

Project Description

The project is run as a collaboration between LTU, Sweden, Nord University, Norway and Kajani University, Finland where the scientific work targets information and communication (ICT/IoT) architectures for data collection, data processing, and data analysis to extract information from complex contexts through statistical models, machine learning (ML) methods, and artificial intelligence (AI). This includes working with performance, scalability, resilience regarding platform architectures, and algorithm performance for AI/ML. The thematic areas addressed are the future's new smart healthcare solutions and e-health processes, which includes activity recognition using sensors and IoT infrastructure, anomaly identification/detection, prediction/forecasting of human behavior and digital tools to improve healthcare processes with close collaboration with municipalities and industry partners especially SMEs.

Duties

You will take Ph.D. courses while performing thesis work in the form of, for example, literature, articles, design studies, construction and programming tasks, theory development, analyses, and presentations. The research area is multidisciplinary and of both scientific and applied nature. Scientific work is presented in English in articles in scientific journals and at international conferences.

Eligibility for third-cycle (doctoral) studies requires that the applicant has completed a second-cycle (Master’s) degree, has completed courses amounting to at least 240 higher education credits, of which at least 60 credits are at the second-cycle level, or has otherwise acquired substantially equivalent knowledge in Sweden or abroad, in accordance with Chapter 7, Section 39 of the Swedish Higher Education Ordinance (SFS 2010:1064).

We are looking for a skilled, analytical, and motivated colleague who can conduct advanced research both independently and in collaboration with others in our research group.

You should have good knowledge of software development and computer science, as well as strong oral and written communication skills in English. Additional knowledge of mathematics, ICT/IoT architectures, and Swedish is considered an advantage. Previous research experience and publications are also considered meritorious.

Selection among applicants who meet the eligibility requirements shall be based on their ability to benefit from the doctoral education. However, the fact that an applicant is considered able to receive credit for previous education or professional experience may not, in itself, give the applicant preference over other applicants in the selection process, in accordance with Chapter 7, Section 41 of the Swedish Higher Education Ordinance (SFS 2010:1064). LTU’s local guidelines, as set out in the admission regulations for doctoral education, shall also apply.

The following selection criteria apply for admission to doctoral education in Distributed Computing Systems:

Good knowledge of English. Good knowledge of software engineering. Ability to independently drive work forward. Ability to collaborate effectively. Ability to analyze and work with complex issues.

For further information about a specific subject see: General syllabus for the Board of the faculty of science and technology

Further information

Employment as a PhD student is limited to 4 years. As a doctoral student, you may, to a limited extent (maximum 20%), perform departmental service within, e.g., teaching and administration, which extends the employment for a corresponding period. Placement: Skellefteå. Starting: According to agreement.

For each position, a preliminary salary range is provided based on the requirements, responsibilities, and market conditions associated with the role.

For further information, please contact

Associate Professor Saguna Saguna, +46 910-585385, saguna.saguna@ltu.se,

Professor, Head of Subject Christer Åhlund, +46 910-585331 christer.åhlund@ltu.se

Union representatives

In case of different interpretations of the English and Swedish versions of this announcement, the Swedish version takes precedence.

Application

The application is made to Luleå University of Technology's recruitment system. We prefer that you apply for this position by clicking on the apply button below. The application should include a CV, personal letter and copies of university masters and bachelors degrees. Copies (up to 3) of previously published scientific articles can be attached. Mark your application with the reference number below. Your application, including diplomas, must be written in English or Swedish.

Closing date for applications: 21 October, 2026

Reference number: 4702-2026