PhD student position in computer science (HINTS) - Theme D

Blekinge Institute of Technology is a place of curiosity and ingenuity with a campus in the middle of the Blekinge archipelago. Here we offer education from undergraduate to doctoral level and conduct world-class applied research. We change and make a difference. Do you want to become one of us?

The Department of Computer Science (DIDA) is one of three departments at the Faculty of Computing. The department is BTH's largest department at BTH with 70 people. At the department, research is conducted in two major areas: computer science and engineering and visual and interactive computer science. There are a number of different research projects in both areas.

Work description

The Ph.D. position is part of a national research project "Human-Centered Intelligent Realities (HINTS)" which is being carried out together with seven industrial partners and is externally funded by the Knowledge Foundation. In co-production with our corporate partners and the community, we develop concepts, principles, methods, algorithms, and tools for human-centered intelligent realities, to lead the way for future immersive, user-aware, and smart interactive digital environments. The project is divided into five separate Research Themes (A-E), which collaborate within the framework of sub-projects. The doctoral position in this call will primarily be involved in Research Theme D.

Research themes in HINTS:
• Research Theme A: Novel Experience Assessment Methodologies for Intelligent Realities
• Research Theme B: Novel Environment and Interaction Techniques for Intelligent Realities
• Research Theme C: Visual Analytics for Intelligent Realities
• Research Theme D: Adaptive and Distributed AI for Intelligent Realities
• Research Theme E: Networking for Intelligent Realities

This PhD research focuses on developing adaptive and distributed AI models for intelligent environments. The primary area of research involves developing AI models that can learn to represent real-world phenomena based on various types of observations, including video, audio, and sensor data. These AI models move beyond conventional predictive and purely data-driven approaches by seeking to capture the underlying causal, spatial, temporal, and semantic relationships that govern real-world phenomena, thereby providing a foundation for context-aware perception, reasoning, and decision-making. The research aims also to address the limitations of existing single-source sensing and purely data-driven methods, which often lack robustness, interpretability, and reliability in uncertain and noisy conditions. To overcome these challenges, the PhD will explore multimodal sensor fusion, uncertainty-aware learning, and distributed collaborative intelligence mechanisms that integrate heterogeneous data sources.

The doctoral student is expected to collaborate with other themes and our industry partners within the employment framework. The main duties of Ph.D. students are to devote themselves to their research studies, which include participating in research projects and third-cycle courses (no less than 80%). The work duties may also include teaching and other departmental duties (no more than 20%). The project involves regular business trips to meetings with our project partners and to international conferences.

Eligibility requirements

To be employed as a Ph.D. student, it is required that the applicant is or will be admitted to postgraduate education.

Eligible for admission to postgraduate education is a person who has completed a degree at an advanced level in a technical, mathematical, or scientific field or who has otherwise acquired knowledge to be able to benefit from postgraduate education in the subject.

Meriting competencies and experience

In addition to the requirements described in the work description, eligibility requirements and assessment criteria for the position, the following degrees, competencies and experiences are considered meritorious:
• Hold a Master's degree in computer science, AI, ML, data science, or equivalent subject.
• Demonstrate proficiency in English (reading, writing, speaking).
• Show ability to work independently as well as in a team.
• Good knowledge in AI, machine learning, data science and mathematics.
• Good knowledge in one or more of the following areas: IoT, data mining, cloud/edge/fog computing.
• Good knowledge in one of the following programming languages: C/C++, Python.

Place of employment: Karlskrona.

Employment level: 100%.

Commencement: Preferred start date 2026-09-15 (or to be agreed).

Duration: Fixed-term for 2.5 years or until the licentiate degree is completed. Funding for the doctoral position is secured until the licentiate degree. If the licentiate degree is successfully completed and continued funding is obtained, there is an opportunity to continue the doctoral studies towards a PhD.

Application deadline: 2026-08-15.

Your application should contain the following:
• A personal cover letter.
• A statement of your background, knowledge and experience in the area(s) relevant to the position.
• A CV.
• Certified degree certificates and transcripts that are officially issued by your university; see universityadmissions.se for official recommendations.
• Contact information for two references.
• The earliest date you can start to work.
• An appendix with current publications (if applicable).
• A link to your thesis (latest/highest degree).

You apply online through our recruitment system by clicking on the "apply" button below.

If you have protected personal data, you should not register your application in our recruitment system. Instead, contact the HR Partner listed as the contact person in the advertisement for further instructions.

Instructions to applicants can be found at https://www.bth.se/english/about-bth/work-at-bth/vacancies. It is the responsibility of the applicant to ensure that the application is complete in accordance with the advertisement and instructions.

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

Blekinge Institute of Technology, BTH, embraces diversity and welcomes applicants with varying backgrounds and experiences.
We work actively to take advantage of the qualities that diversity and an even gender distribution contribute to our operations.

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Contact person

Veronica Sundstedt

Project leader/Senior lecturer

+46455385850

veronica.sundstedt@bth.se

Bo Peterson

Prefekt/Head of Department

+46455385755

bo.peterson@bth.se

Lina Göransson

HR-specialist

+46455385029

Mikael Åsman

Union representative (SACO)

+46455385720

mikael.asman@bth.se

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