Linnaeus University
Doctoral studentship in Computer and Information Science
Linnaeus UniversitySweden20 hours ago
Full-timeInformation Technology
Welcome to Linnaeus University! Here you'll meet 2 200 staff members and 40 000 students, all united in following the vision to set knowledge in motion for a sustainable societal development. With us, research and education are conducted with an eye towards the future. Our proximity to the business world, both locally and globally, gives us a wide reach and the ability to create change that makes an impact. All that's needed is a place where ideas have the space to meet and grow. That's what we've created – and you are invited.

Change starts here!

The Faculty of Technology is one of five faculties at Linnaeus University. We bring together the university's education and research in technical subjects. Our operations are organised into nine departments and a faculty office. We also house the Linnaeus University Centre DISA and two Linnaeus Knowledge Environments: Green Sustainable Development and Digital Transformations. Several of the faculty's research groups collaborate within the strategic research area of Forest Values.

The Department of Computer Science and Media Technology is responsible for many educational programs at basic and advanced levels within computer science, software engineering, and media technology. Currently, more than 60 staff members work in the department. The department has a strong connection with other departments of Linnaeus University and industrial and public partners.

Subject area for the position: Computer and information science

Location until further notice: Växjö . Since Linnaeus University is located in both Växjö and Kalmar, travel between the two may be required.

Term and hours: The doctoral studentship is limited in time in accordance with the Higher Education Ordinance (Chapter 5, Section 7). The studentship is full-time.

Starting date: Starting date as agreed upon.

Job Description

The Department of Computer Science and Media Technology is recruiting a doctoral student to contribute to the Swedish Research Council's research project, "Simulating Urban Dynamics: Visualization and Networks for Epidemiology and Societal Impact in Sweden". In addition, the doctoral student will contribute to the research program FORECAST – AI-Driven Integration and Forecast of Forest Supply Data for Sustainable and Climate-Resilient Value Chains , funded by The Bridge initiative. This project focuses on AI-driven data integration, forecasting, scenario simulation, and visual decision-support systems for sustainable forest-based supply chains in close collaboration with industrial partners. These projects aim to develop interactive methods, computational models, artificial intelligence models, and visual analytics tools that integrate urban data, forestry data, temporal and multivariate network modelling, and simulation of infection dynamics in Swedish city environments.

The doctoral student will work on the design and implementation of interactive web-based and/or immersive analytics environments that integrate temporal networks, heterogeneous spatial-temporal data, and AI-driven forecasting and simulation models. These environments will support the modelling and analysis of infectious disease spread in urban settings as well as sustainability assessment and data-driven decision-making in forest-based supply chains, using real urban, demographic, forest, and supplier data. The work includes constructing and processing heterogeneous spatial-temporal and supplier datasets; designing knowledge-graph-based data models for integrating diverse urban, forest, and market data; developing AI-based forecasting and scenario-simulation pipelines that combine machine learning and simulation methods; and creating visual analytics and human-in-the-loop decision-support interfaces. These tools will support public health authorities, urban planners, policymakers, sustainability analysts, and industry stakeholders in interpreting outcomes, exploring intervention and scenario strategies, and improving decision-making. Interfaces may include web platforms, large-display environments, or other immersive analytics solutions to enhance exploration and collaborative reasoning.

The position offers the opportunity to work at the intersection of computer science, visualization, forestry, public health, and societal impact. It also provides the opportunity to contribute to sustainable forest-based value chains, climate-resilient supply-network planning, and data-driven industrial decision-making through advanced AI and visual analytics methods. The doctoral student will participate in studies and discussions with stakeholders and domain experts, contribute to the dissemination of scientific results, and collaborate with national and international partners in the areas of visualization, epidemiology, and urban data research. The student will also collaborate with industry partners in the forest and supply-chain sectors through co-design workshops, prototype evaluations, and technology-transfer activities, ensuring that research results translate into practical decision-support tools. The candidate is expected to conduct independent scientific work and produce high-quality publications.

The Higher Education Ordinance states that anyone who is employed as a doctoral student shall primarily devote themselves to their own studies, although they may, to a limited extent, also work with education, research, and administration. Before a doctorate has been awarded, such work may not exceed 20% of full-time work.

Eligibility

A person meets the general entry requirements for third-cycle studies if they

  • have been awarded a degree at the second-cycle level
  • have at least 240 credits of passed courses, of which at least 60 credits are at the second cycle level; or
  • have acquired essentially equivalent knowledge in some other way, in or outside Sweden.

Specific prerequisites for admission to graduate studies in Computer and Information Science are required:

  • approved courses of a minimum of 90 credits in the subject Computer and Information Science or the equivalent, and
  • an individual study project of a minimum of 15 credits in the subject Computer and Information Science, or the equivalent.

Other Requirements

  • independence and ability to solve challenging problems.
  • excellent work ethic and commitment to the job.
  • excellent English skills, both written and verbal.

Desirable Qualifications (Good To Have, But Not Mandatory)

  • Experience or strong interest in information visualization, visual analytics, and/or human-computer interaction – particularly for decision-support systems or analytical tools;
  • Experience or interest in immersive analytics (e.g., interactive tabletops, spatial user interfaces, or large-display decision-support environments).
  • Knowledge of network science, knowledge graphs, temporal networks, graph-based modelling, or complex systems;
  • Experience with simulation (e.g., epidemiological spread, agent-based models, or dynamic processes on networks), or AI-based time-series and scenario modelling;
  • Experience or strong interest in game development or game engines (e.g., Unity or similar), serious games, or interactive simulations, with the goal of developing simulation platforms, digital twins, or exploratory scenario-based environments for analysis and decision support;
  • Familiarity with geospatial or urban datasets, environmental, supplier, or market datasets, or methods for integrating multivariate or temporal data sources;
  • A demonstrated track record of scientific publication or the clear potential to publish in peer-reviewed venues, particularly in areas related to visualization, data science, artificial intelligence, or computational modelling;
  • Programming experience relevant to data-intensive systems and visualization prototypes (e.g., interactive front-end development, web environments, data processing, or scientific computing);
  • Experience or strong interest in artificial intelligence and machine learning for data integration, forecasting, or decision support;
  • Interest in interdisciplinary research involving public health, urban planning, sustainability, or industrial and societal applications of computing and AI;
  • Strong communication skills and motivation to collaborate with stakeholders and domain experts, and to contribute to research publications, prototyping, and evaluation activities.
  • Familiarity with research methodologies and literature reviews.
  • Ability to work collaboratively in a multidisciplinary team.
  • Strong organizational skills, self-motivation, initiative, attention to detail, and flexibility, with the ability to prioritize tasks and meet deadlines.
  • Swedish language skills are a merit but not a must requirement.

Assessment criteria

  • Applications to graduate studies are governed by rules in the admission regulations.
  • The selection of candidates is made with regard to the applicant’s ability to successfully complete and benefit from their studies at the graduate level. The assessment takes into account academic skills documented in scientific works, especially focused on the quality of the essays at the undergraduate level, any advanced work and other scientific or scholarly works. The assessment also takes into account breadth and composition of the undergraduate degree as well as the picture which the intended principal academic supervisor, examiner, and other colleagues in the research group and the subject obtained of the applicant’s potential.
  • The applicants are ranked by a review group appointed by the subject.

You are welcome to submit your application no later than March 26th, 2026.

Contact

Head of department: Arianit Kurti, [email protected]

Assistant supervisor: Claudio Linhares, [email protected]

Assistant supervisor: Amilcar Soares, [email protected]

HR partner: Erika Hjelmer, [email protected]

Would you like to know more about the Faculty of Technology Office/? Learn more at Lnu.se, https://lnu.se/en/ .

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