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Blekinge Institute of Technology (BTH) is a place for curiosity and ingenuity, with its campus located in the heart of the Blekinge archipelago. Here we offer education from undergraduate level to doctoral degrees and conduct world-class applied research. We change and make a difference. Do you want to join us?

The Department of Computer Science is one of three departments at the Faculty of Computer Science. It is BTH's largest department with approximately 70 employees. Research is conducted at the department within two major areas: computer science and computer systems technology, as well as visual and interactive computer science. Various research projects are ongoing within both areas.

Job Description

The doctoral position is part of the national research project "Human-Centered Intelligent Realities (HINTS)", which is carried out in collaboration with seven industry partners and is externally funded by the KK Foundation. In collaboration with our corporate partners and society, we develop concepts, principles, methods, algorithms, and tools for human-centered intelligent realities, paving the way for future immersive, user-aware, and smart interactive digital environments. The project is divided into five separate research themes (A–E) that collaborate within the framework of sub-projects. The doctoral position in this call will primarily be linked to Research Theme D.

Research Themes within HINTS:

• Research Area A: New methods for evaluating experiences in intelligent realities
• Research Area B: New environment and interaction technologies for intelligent realities
• Research Area C: Visual analytics for intelligent realities
• Research Area D: Adaptive and Distributed AI for Intelligent Realities
• Research Area E: Network technology for intelligent realities

This doctoral research focuses on developing adaptive and distributed AI models for intelligent environments. The primary research area involves the development of AI models that can learn to represent phenomena in the real world based on different types of observations, including video, audio, and sensor data. These AI models go beyond conventional predictive and purely data-driven approaches by attempting to capture the underlying causal, spatial, temporal, and semantic relationships that govern phenomena in the real world, thereby laying the foundation for context-aware perception, reasoning, and decision-making. The research also aims 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 doctoral candidate will explore multimodal sensor fusion, uncertainty-aware learning, and distributed mechanisms for collaborative intelligence that integrate heterogeneous data sources.

The doctoral candidate is expected to collaborate with other research areas and our industry partners within the scope of the employment. The doctoral candidate's main tasks are to engage in their research studies, which includes participation in research projects and courses at the doctoral level (at least 80 %).

The tasks may also include teaching and other institutional duties (maximum 20 %). The project involves regular business trips to meetings with our project partners and to international conferences.

Qualifications

To be employed as a doctoral student, the applicant must be or become admitted to doctoral studies.

Eligible for admission to doctoral studies is anyone who has completed an advanced level degree in a technical, mathematical, or natural science field, or who has otherwise acquired knowledge to be able to benefit from doctoral studies in the subject.

Qualifications and Experience

In addition to the requirements described in the job description, qualification requirements, and assessment criteria for the employment, the following degrees, competencies, and experiences are considered meritorious:

• Hold a master's degree in computer science, AI, ML, data science, or a corresponding subject.
• Demonstrate good knowledge of English (reading, writing, speaking).
• Demonstrate ability to work both independently and in a team.
• Good knowledge of AI, machine learning, computer 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 Work: Karlskrona.

Extent of Employment: 100 %.

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

Start Date: Recommended start 2026-09-15 or as agreed.

Application Deadline: 2026-08-15.

Your application should include:

• A statement of your background and experience in the relevant areas.
• A curriculum vitae (CV).
• Degree and course certificates officially issued by your educational institution.
• A statement of your background, knowledge, and experience in the area or areas relevant to the position.
• Contact details for two reference persons.
• The earliest date the employment can begin.
• An attachment with existing publications (if relevant).
• A link to your thesis (latest/highest degree).

You apply via our recruitment system by clicking 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 more information. Instructions for applicants can be found at https://www.bth.se/om-bth/jobba-hos-oss/lediga-jobb (https://www.bth.se/om-bth/jobba-hos-oss/lediga-jobb). As an applicant, you are responsible for ensuring the application is complete in accordance with the advertisement and instructions. BTH welcomes applicants with different backgrounds and experiences. We actively work to capitalize on the qualities that diversity and equal gender distribution bring to the organization. We have chosen media for this recruitment and therefore decline contact with advertising salespeople or other sellers of recruitment services.