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- PhD Student in the LärA-AI Graduate School at Uppsala University
PhD Student in the LärA-AI Graduate School at Uppsala University
Uppsala UniversitetUppsala län, Uppsala
19 days left
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Please note that this is a shortened version of the advertisement.
To see the full advertisement, please click on "Apply here" or visit here (https://www.uu.se/om-uu/jobba-hos-oss/lediga-jobb).
Do you want to research digital working environments in schools, supported by competent and friendly colleagues in an international setting? Do you want an employer that invests in sustainable employment and offers secure, favorable working conditions? Welcome to apply for a position as a PhD student in the LärA-AI graduate school at Uppsala University.
You will be one of nine PhD students in the LärA-AI graduate school (The Working Environment of the Teaching Profession in an AI-Transformed School). The focus of the graduate school is to investigate how generative artificial intelligence (GenAI) affects teachers' working environment and professional role. When GenAI systems are used in planning, assessment, and decision-making, both teachers' tasks and how the work is experienced change. At the same time, research shows that many teachers already have a pressured work situation with high workloads and increased administrative demands. Therefore, new knowledge is needed on how GenAI affects working conditions, responsibilities, and competence needs.
Tasks
The position is linked to the graduate school's third theme: Collegial Learning, Digital Competence, and Professional Development. Your focus will be on exploring the question "What do we need to know?" through teachers' perceptions and expressions of knowledge and AI competence from an organizational support perspective. The research will investigate what teachers perceive as essential AI competence, focusing on how support structures take into account diversity in teachers' digital preparedness, previous experience, and educational background.
You will primarily collaborate with two other PhD students in this theme, but all three themes will be closely integrated to establish a holistic understanding of how AI development affects teachers' working environment and professional role. You are expected to actively participate in the graduate school's joint activities, such as courses, seminars, workshops, and international summer schools, as well as contribute to the research environment through joint discussions and collaboration.
You will mainly focus on your own doctoral education within the framework of the graduate school. Other duties at the department, such as teaching and administrative work, may be included within the framework of the employment (max 20%).
Qualification requirements
Basic eligibility for doctoral education is met by those who:
- have obtained a degree at the advanced level in computer science, information technology, education, pedagogy, working life science, or another subject area relevant to the position, or
- have completed at least 240 higher education credits, of which at least 60 higher education credits at the advanced level including an independent project of at least 15 higher education credits, or
- have acquired equivalent knowledge in some other way.
The university may grant exceptions to the basic eligibility requirement for an individual applicant if there are special reasons. (Chapter 7, Section 39 of the Higher Education Ordinance). For specific eligibility, see here (https://www.uu.se/medarbetare/fakultet/teknisk-naturvetenskapliga/utbildning-och-undervisning/utbildning-pa-forskarniva/amnen-och-studieplaner/amnen/datavetenskap-med-inriktning-mot-datavetenskapens-didaktik).
Other requirements:
- Excellent written ability, with documented ability to formulate and structure academic texts in English.
- Strong analytical, problem-solving, and communication skills.
- Ability to work both independently and in groups, in interdisciplinary and multicultural contexts.
- High motivation and good work capacity, with the ability to work purposefully and persistently on complex research tasks.
- Interest in pedagogical innovation and the role of technology in learning.
Desirable/meritorious otherwise
- Documented ability to conduct independent research (e.g., literature reviews, qualitative or quantitative data collection/analysis).
- Familiarity with theories of workplace learning, sociocultural perspectives, and groundbreaking technologies in society.
- Experience with digital technologies, especially for teaching purposes.
- Understanding of AI concepts and applications in education.
- Teaching experience.
- Very good knowledge of Swedish, both spoken and written, as data collection, analysis, and collaboration occur in a Swedish-speaking context.
Regulations for doctoral students can be found in the Higher Education Ordinance Chapter 5, Sections 1-7 and at here (https://regler.uu.se/?languageId=3).
About the position
The position is temporary, according to HF Chapter 5, Section 7. The extent is full-time. Start date May 1, 2026, or by agreement. Place of employment: Uppsala.
For inquiries about the position, please contact: Calkin Suero Montero, +46 18 4715447, [email protected].
Welcome with your application by February 23, 2026, UFV-PA 2026/298.
Uppsala University is a broad research university with a strong international position. The ultimate goal is to conduct education and research of the highest quality and relevance to make a difference in society. Our most important asset is all 7,600 employees and 53,000 students who, with curiosity and commitment, make Uppsala University one of the country's most exciting workplaces.
Read more about our benefits and what it is like to work at Uppsala University here (https://uu.se/om-uu/jobba-hos-oss/).
The position may be subject to security screening. A prerequisite for employment in the case of security screening is that the applicant is approved.
We kindly decline offers of recruitment and advertising assistance.
Applications are accepted in Uppsala University's recruitment system.
Union representatives: Saco-S - [email protected], Seko - [email protected], ST (OFR/S) - [email protected]
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