PhD Position

Will your research enable responsible AI adoption for SMEs?

Are you interested in implementing and evaluating AI systems that generate productivity gains while remaining transparent, accountable, and aligned with organizational autonomy?

Small and medium-sized enterprises account for more than 65% of Dutch employment, yet productivity growth has stagnated and digital adoption remains uneven. Artificial Intelligence offers major opportunities for productivity and innovation. However, AI only creates value when it is rigorously evaluated, responsibly implemented, and auditable in practice.

About the Project

This PhD project focuses on measurable AI-driven impact in SMEs. The aim is to contribute to the design, implementation, and evaluation of AI systems that:

• generate productivity gains
• remain transparent and accountable
• support organizational autonomy

A central innovation of the project is the development and validation of an agentic AI-based survey instrument enabling scalable, high-resolution data collection across up to 10,000 SMEs.

The project combines:

• large-scale econometric impact evaluation
• responsible AI system design
• governance and auditing approaches

The research is embedded in the national AI adoption initiative:

https://www.ai-injebedrijf.nl/

and connected to broader Dutch and European digital autonomy programmes.

Close Link with Existing Projects

The PhD researcher will work with data from challenge-based learning projects.

The faculty is rapidly expanding this approach:

• 30 projects last year
• 60 projects this year
• target of approximately 200 projects annually by 2030

In these projects, students design prototype analytics and AI solutions, creating valuable data on AI adoption and digital autonomy.

Additionally, UvA Economics and Business is a core partner of the “AI in je bedrijf” project, where students design prototype solutions for SMEs.

The pilot project launched with:

• 30 SMEs
• 150 UvA students

A scale-up plan aims to support 10,000 SMEs in the Netherlands over the next 5 years.

Main Duties and Responsibilities

You will spend:

• 80% of your time on research
• 20% on teaching at the Amsterdam Business School

Responsibilities

• Participate in field interventions investigating barriers and drivers of AI and digital technology adoption in SMEs
• Research AI adoption through the lens of:
  • Conduct large-scale econometric and statistical analyses using data from 10,000 SMEs
  • technology
  • productivity
  • digital autonomy
• Develop an AI solution taxonomy for SMEs supporting:
  • Co-create an agentic AI-based survey system and compare it with traditional survey techniques
  • responsible adoption
  • auditing
  • knowledge sharing
• Create open data and software tools supporting AI adoption in SMEs
• Present findings at international conferences
• Publish in leading international journals
• Complete a PhD dissertation within four years
• Attend classes and seminars to strengthen research skills
• Participate in departmental research activities
• Assist in knowledge dissemination activities
• Contribute to teaching activities, including:
  • undergraduate tutorials
  • supervision of BSc thesis projects

Candidate Profile

This interdisciplinary project combines:

• technical development (AI and analytics)
• business administration (adoption and productivity)
• information systems (governance and digital autonomy)

Candidates are expected to have strength in at least one of these areas and interest in the others.

We Are Looking For Someone Who

• Thrives at the intersection of AI and real-world impact
• Enjoys translating technical possibilities into practical SME solutions
• Collaborates effectively with diverse teams
• Conducts rigorous and curiosity-driven research
• Communicates complex ideas clearly to academic and non-academic audiences
• Takes initiative in dynamic environments
• Balances independent research with collaborative work

Additional Advantage

Experience with:

• Python or R
• data science methods
• econometric modelling
• natural language processing
• large-scale survey and transcript analysis

Formal Requirements

A Master’s degree in one of the following fields (or related disciplines), completed by September 2026:

• Statistics
• Econometrics
• Computer Science
• Artificial Intelligence
• Data Science
• Mathematics
• Information Systems
• Technical Business Administration

What We Offer

• A 4-year temporary contract for 38 hours per week
  • Opportunity to complete a PhD dissertation
  • initial contract: 18 months
  • extension after satisfactory evaluation
• Gross monthly salary between:
  • €3,059 (1st year)
  • €3,881 (final year)
• Additional:
  • Possible eligibility for the Dutch “30% ruling” tax benefit for international applicants
  • 8% holiday allowance
  • 8.3% year-end allowance
• Access to a unique large-scale SME dataset and intervention programme
• Participation in a national AI initiative
• Vibrant research environment in central Amsterdam

Additional Benefits

• 29 vacation days annually
• Additional holidays between Christmas and New Year
• Excellent work-from-home facilities
• Reimbursement of commuting expenses
• Pension accrual with ABP
• Extensive study and development opportunities
• Participation in open UvA lectures (up to 30 credits annually)

PhD Supervision Team

The successful candidate will be supervised by:

• Inez Zwetsloot
  Statistical evaluation and validation of AI-driven systems
• Bart Lameijer
  Management and implementation of AI and productivity technologies
• Paul van Vulpen
  Digital autonomy, decentralized governance, and responsible technology design

Application Information

Applications are reviewed on a rolling basis.

Required Documents

Please submit:

• Cover letter (PDF)
• Resume/CV (PDF)

Applications submitted after the deadline, incomplete applications, or applications not submitted through the official link cannot be considered.

In case of equal suitability, internal candidates will be given priority.

Contact Information

Dr. Inez Zwetsloot

E-mail: i.zwetsloot@uva.nl
Telephone: +31 6 305 668 33