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

Blekinge Institute of Technology; Karlskrona kommun; On-site; SEK 357,000 - 469,000; Full time

Job summary

Blekinge Institute of Technology invites applications for a Ph.D. position within the national research project HINTS (Human-Centered Intelligent Realities).

The work focuses on developing adaptive and distributed AI models to learn from multimodal observations and to support context-aware perception, reasoning, and decision-making in intelligent environments. The PhD is part of Research Theme D and involves collaboration with industrial partners.

Qualifications

• 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.

Skills

AI/ML

Data science

Mathematics

IoT

Data mining

Cloud/edge/fog

C/C++

Python

Teamwork

English proficiency

Education

Master's degree in computer science/AI/ML/data science

Tools

C/C++

Python

Job description

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.

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

• 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.

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.

We have chosen media for this recruitment and therefore we reject contact with advertisers or sellers of recruitment services.

Contact person

Veronica Sundstedt

Project leader/Senior lecturer

[phone]

[e-mail]

Bo Peterson

Prefekt/Head of Department

[phone]

[e-mail]

Lina Göransson

HR-specialist

[phone]

Mikael Åsman

Union representative (SACO)

[phone]

[e-mail]

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