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Mattias Wiggberg

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2 weeks ago

Doctoral student in technology foresight and digital skills forecasting KTH Royal Institute of Technology in Sweden

Degree Level

PhD

Field of study

Computer Science

Funding

Available

Deadline

Mar 11, 2026

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Country

Sweden

University

KTH Royal Institute of Technology

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Where to contact

Official Email

Keywords

Computer Science
Information Technology
Mathematics
Empirical Research
Business
Industrial Engineering
Management
Automation
Industrial Economics
Robotics
Expert Elicitation
Economics
Statistics
Machine learning

About this position

The Department of Industrial Economics and Management (INDEK) at KTH Royal Institute of Technology invites applications for a doctoral student position focused on technology foresight and digital skills forecasting. This research opportunity centers on forecasting future skill needs in industrial companies undergoing advanced digitalisation, with particular emphasis on AI, automation, and robotics. The project aims to develop and apply quantitative and hybrid forecasting methods to analyze the evolution of tasks, roles, and skill requirements in environments where work is increasingly hybridized between humans, AI systems, and automated technologies (AI-augmented work).

A central aspect of the research is method development, combining statistical, machine-learning-based, and data-intensive approaches with qualitative and participatory foresight methods such as scenario planning and expert elicitation. The doctoral student will work closely with industry partners in projects funded by Vinnova’s advanced digitalisation programs, gaining access to empirical data from real-world industrial settings and engaging in extensive industry interaction. Collaboration with internationally leading academic environments is also part of the research experience.

The position is embedded in an interdisciplinary research environment at INDEK, with strong links to management research, systems thinking, digital transformation, and work and employment studies. The research will contribute to the rapidly developing field of technology foresight and digital skills forecasting, playing a key role in advancing both academic and practical understanding of AI-augmented work.

Supervision will be provided by Associate Professor (Docent) Mattias Wiggberg. The position is full-time and offers a monthly salary according to KTH’s doctoral student salary agreement, along with employee benefits. The employment is for up to four years, with the possibility of renewal according to university regulations.

Applicants must meet the admission requirements for postgraduate education, including a second cycle degree or equivalent, documented knowledge of quantitative methods (statistics, econometrics, data analysis, machine learning, forecasting), and experience in empirical research. At least 60 credits at the second-cycle level in Industrial Economics and Management or directly relevant subjects are required, or equivalent knowledge acquired in other ways. English proficiency equivalent to English B/6 is mandatory. Meritorious qualifications include experience with forecasting models, hybrid approaches, bibliometric analysis, scenario methodologies, AI-related applications, and collaboration with industry or the public sector. Personal skills such as independence, collaboration, professionalism, and analytical ability are emphasized during the selection process.

To apply, candidates must submit a complete application through KTH’s recruitment system, including a CV, application letter, certified copies of diplomas and grades, proof of language requirements, a research outline, and representative publications or technical reports. The application deadline is March 11, 2026. For further information, contact Associate Professor Mattias Wiggberg at [email protected].

KTH Royal Institute of Technology is a leading international technical university located in Stockholm, Sweden, offering a creative and dynamic environment with good working conditions and attractive benefits. The university values equality, diversity, and equal opportunities as integral to its core values.

Funding details

Available

What's required

Applicants must have a second cycle degree (e.g., master's) or equivalent, or at least 240 higher education credits with at least 60 at the second-cycle level. Documented knowledge of quantitative methods such as statistics, econometrics, data analysis, machine learning, and forecasting is required. Experience in empirical research is mandatory. At least 60 credits at the second-cycle level in Industrial Economics and Management or directly relevant subjects are required, or equivalent knowledge acquired in other ways. English proficiency equivalent to English B/6 is mandatory. Meritorious qualifications include experience with forecasting models, hybrid approaches, bibliometric analysis, scenario methodologies, AI-related applications, and collaboration with industry or the public sector. Personal skills such as independence, collaboration, professionalism, and analytical ability are emphasized.

How to apply

Apply through KTH's recruitment system using the provided application link. Ensure your application includes a CV, application letter, certified copies of diplomas and grades, proof of language requirements, a research outline, and representative publications or technical reports. Submit your application by the deadline.

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