PhD student in education

Jönköping University is looking for a PhD student for the research project WAIT. Take the opportunity to develop in an interdisciplinary environment!

WE OFFER YOU

Jönköping University (JU) is a modern university characterized by internationalization and entrepreneurial spirit. We have well-qualified, inventive and enterprising employees from all over the world. With us, you will experience a creative interdisciplinary environment with good opportunities for personal development.

The PhD project is located at the School of Learning and Communication (HLK) and is run in collaboration with Jönköping University (JTH), at JU. Organizationally, the doctoral student will belong to the research environment and the collaboration node Encell, where research on lifelong learning is carried out, related to, among other things, skills supply, education and professional development. 

The PhD student will be part of the research theme “Learning and Digitalization” at HLK and a member of the national and international consortium for graduate schools GRADE, as well as having access to the international center of excellence AILI - AI in Learning and Instruction (2024-2028). At JTH, AI research is conducted at the Department of Computer Science and also within Jönköping AI Lab (JAIL). Through these connections, the PhD student will receive supervision and access to the very latest research in AI technologies and learning. 

The PhD student will be involved in and benefit from a larger PhD group in GRADE research. In addition, a “twin doctoral student” will be admitted simultaneously at Mid Sweden University, also focusing on GRADE research and with similar prerequisites, allowing co-learning of courses and continuous knowledge exchange. 

The project of the PhD student is relevant to teaching carried out in master's and undergraduate programs at HLK and JTH. The doctoral student is expected to contribute to the research environment through, for example, seminar participation and participation in joint activities. 

THIS IS WAIT

WAIT is an interdisciplinary project that bridges gaps between technical and social sciences, offering frameworks to promote lifelong learning and to enhance AI’s role in education and workplaces. By doing so, the WAIT project seeks to empower individuals and institutions to adapt to digital transformations and leverage AI for innovation and professional development.  

The expansion of AI and digital transformation raises fundamental questions about what, where, and how learning should occur, with a particular focus on developing professional AI-gency. This concept refers to professionals’ ability to engage with AI systems to enhance collaboration, creativity, and decision-making. 

Thus, the project is situated at the intersection of workplace learning and higher education. It explores how AI impacts career trajectories and professional development and how workplaces and educational institutions support digital transformations. A key question is how leaders can facilitate learning linked to AI and how employees experience and manage AI-driven changes.

The WAIT project is organized around three key studies.  

• First, it examines the role of higher education in supporting digital transformation and developing AI competencies.  
• Secondly, it investigates leadership’s role in fostering AI-agency and enabling effective AI learning in workplaces.  
• Thirdly, it addresses how AI learning is integrated into professional practices and how such practices evolve in response to AI.

REQUIREMENTS

The PhD candidate has an educational background in pedagogy or related disciplines, such as work science, improvement science, organizational science, informatics or equivalent. We would like the PhD candidate to have experience and interest in workplace learning and digital transformations, in the business or public sector.   

General entry requirements for third-cycle studies is that you have been awarded a degree at second-cycle level, achieved at least 240 credits, of which a minimum of 60 credits must have been achieved at second cycle level, or otherwise acquired equivalent knowledge in Sweden or abroad. You must have completed an independent project of at least 15 credits relevant to the subject.

Furthermore, we look for you to possess:

• 90 credits in education or other subject relevant to the focus of the research project or relevant professional experience deemed equivalent   
• Good ability to apply a reflective and analytical approach to your work 
• Proficient in academic-level English (verbal and written) 
• Cooperation and collaboration skills 
• Communication and initiative skills  

It is an advantage if you have experience relevant to the focus of the project, good knowledge of Swedish or Scandinavian languages, experience of research-related activities, such as data collection and experience of analytical work and report and article writing. 

In the assessment, personal suitability for the position will weigh heavily.

INFORMATION

The doctoral program comprises four years of full-time doctoral studies but is normally carried out over a period of five years as it also includes departmental service, teaching or similar of a maximum of 20 percent. 

The PhD position is full-time with start, 2025-08-11, or as agreed. The employment is extended annually based on the individual study plan. The salary and other condition is regulated according to collective agreements. 

HOW TO APPLY

We welcome your application, no later than 2025-03-07. The selection process is conducted continuously, allowing appointments to be made before the final application deadline. Hence, we encourage early submissions.

Please ensure your application, preferably in PDF format through our recruitment system, includes the following documents:

• Curriculum Vitae (CV)
• Motivation letter or Cover letter
• Certified certificates and diplomas
• Scientific publications
• Research outline of maximum 5 pages including problem formulation(s), theoretical and methodological starting points, a preliminary timetable for the implementation of the research work and a clear connection to the development of professional AI competence. The plan will be assessed for originality, scientific relevance and feasibility. 
• References