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EURAXESS

PhD position in Agent-based Modelling for Inspection Simulations

The Human Resources Strategy for Researchers
19 Apr 2024

Job Information

Organisation/Company
Utrecht University
Research Field
Physics
Researcher Profile
First Stage Researcher (R1)
Country
Netherlands
Application Deadline
Type of Contract
Temporary
Job Status
Not Applicable
Hours Per Week
40.0
Is the job funded through the EU Research Framework Programme?
Not funded by an EU programme
Is the Job related to staff position within a Research Infrastructure?
No

Offer Description

Join our exciting research project as PhD candidate at Utrecht University and become part of the research collaboration AI4Oversight Lab which is part of the Innovation Centre for Artificial Intelligence.

Your job
In this PhD position, you will focus on simulating the inspection processes. Strategies that inspectorates use for selection of targets and enforcement in response to non-compliances invoke changes in the behaviour of the target population. In turn, these changes invoke updates in the strategies of the inspectors. It is difficult—if not impossible—to study and test the interactions between an inspectorates’ actions and the behaviour of inspectees outside of a lab setting because of practical and ethical constraints. In this project we aim to develop data-driven agent-based models to study these behavioural dynamics in a synthetic environment, and thereby enabling the evaluation of (data-driven) inspection strategies before field deployment, while testing for effectiveness, robustness, and fairness of target selection strategies.

The Dutch government inspectorates play a critical role in safeguarding public interests such as food safety, a clean environment, fair working conditions, and quality of education. To ensure effective supervision with a limited capacity at strategic and operational level, inspectorates need to work in a data-driven way and embed AI technology in their primary processes. The amount of information is too large and complex to be fully covered by human resources. At the same time, society rightly expects AI to be used in a responsible manner.

By joining the AI4Oversight ICAI lab, you join a collaborative community that addresses AI challenges specific to the inspection domain leading to scientifically assured methods. The AI4Oversight lab connects the Human Environment and Transport Inspectorate (ILT), the Netherlands Labour Authority (NLA), the Inspectorate of Education (IvhO), Netherlands Food and Consumer Product Safety Authority (NVWA), Netherlands Organisation for Applied Scientific Research (TNO), Utrecht University and Leiden University. Collaboration between these organisations is seen as an essential element of our lab. Working together allows not only to develop new knowledge, but also to use each other’s expertise, to experiment together, to learn from each other and to bring theory to practice.

The execution of the research will be highly participatory. You will spend time at the offices of funding partners and have the opportunity to dive into the practical challenges and way of working of the partners. You will work together with data scientists of the practical partners, who will contribute with practical experiences and use cases. The AI4Oversight Lab hosts at least 6 PhD candidates and knowledge exchanges will be held regularly to promote collaboration.

Key responsibilities:

  • conducting original and novel research in the field of data-driven simulations and large-scale agent-based modelling in the domain of government oversight;
  • publishing and presenting scientific articles at international journals and conferences;
  • collaborating with other PhD candidates in the AI4Overisight lab, researchers at the partners’ data science labs, the intended users, and other stakeholders.

Requirements

Specific Requirements

You have a desire to work on applied and societally relevant problems, and bring:

  • an MSc degree in Artificial Intelligence, Data science, Mathematics, Computer science, Computational Sciences, or a relevant field;
  • good programming skills in e.g., Python and Java;
  • preferably a solid experience with agent-based modelling, agent simulations, and/or background in behavioural sciences;
  • excellent written and oral communication skills in English;
  • Dutch proficiency or willingness to learn is a plus;
  • the ability to work with diverse stakeholders, e.g., industry professionals, academic researchers.

Please note that EU citizenship is required for this position.

Additional Information

Benefits

We offer:

  • a position for four years (1.0 FTE);
  • gross monthly salary between €2,770 and €3,539 in the case of full-time employment (salary scale P under the Collective Labour Agreement for Dutch Universities (CAO NU);
  • 8% holiday pay and 8.3% year-end bonus;
  • a pension scheme, partially paid parental leave and flexible terms of employment based on the CAO NU.

In addition to the terms of employment laid down in the CAO NU, Utrecht University has a number of schemes and facilities of its own for employees. This includes schemes facilitating professional development, leave schemes and schemes for sports and cultural activities, as well as discounts on software and other IT products. We also offer access to additional employee benefits through our Terms of Employment Options Model. In this way, we encourage our employees to continue to invest in their growth. For more information, please visit Working at Utrecht University.

Selection process

As Utrecht University, we want to be a home for everyone. We value staff with diverse backgrounds, perspectives and identities, including cultural, religious or ethnic background, gender, sexual orientation, disability or age. We strive to create a safe and inclusive environment in which everyone can flourish and contribute.

If you are enthusiastic about this position, just apply via the 'Apply now' button. Please enclose:

  • your motivation letter;
  • your curriculum vitae;
  • a copy of your Master's diploma;
  • a copy of your Master's thesis;
  • academic transcripts;
  • if you have accepted or submitted publications, state this in your motivation letter and list them with bibliographic information (including DOI) in your CV;
  • the names, affiliations, telephone numbers, and email addresses of at least two referees who have agreed to be contacted.

A background check may be part of the selection procedure.

If this specific opportunity isn’t for you, but you know someone else who may be interested, please forward this vacancy to them.

Some connections are fundamental – Be one of them
#FundamentalConnection

Additional comments

For more information, please contact Dr Mihaela Mitici at m.a.mitici@uu.nl.

Do you have a question about the application procedure? Please send an email to science.recruitment@uu.nl.

Candidates for this vacancy will be recruited by Utrecht University.

Website for additional job details

Work Location(s)

Number of offers available
1
Company/Institute
Universiteit Utrecht
Country
Netherlands
City
Utrecht
Postal Code
3584CC
Street
Princetonplein 5
Geofield

Contact

City
Utrecht
Website
Street
Domplein 29
Postal Code
3512 JE