Agent-based Modelling for Inspection Simulations

UU Select | Utrecht | Vast | Fulltime | www.uu.nl |
PhD position in Agent-based Modelling for Inspection Simulations

Working at Utrecht University

PhD position in Agent-based Modelling for Inspection Simulations

Faculty: Faculty of Science Department: Department of Information and Computing Sciences Hours per week: 36 to 40 Application deadline: 19 May 2024

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.

Your qualities

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.

Our offer

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.

At the Faculty of Science there are 6 departments to make a fundamental connection with: Biology, Chemistry, Information and Computing Sciences, Mathematics, Pharmaceutical Sciences and Physics. Each of these is made up of distinct institutes that work together to focus on answering some of humanity's most pressing challenges.

The Department of Information and Computing Sciences is nationally and internationally known for its research in computer science and information science. The Department provides and contributes to a number of Bachelor's and Research Master's programmes in the fields of Computer Science, Information Science, Data Science and Artificial Intelligence.
The department employs over 200 people in four divisions: Artificial Intelligence & Data Science, Algorithms, Interaction, and Software. The atmosphere is collegial and informal.

For more information, please contact Dr Mihaela Mitici at .

Do you have a question about the application procedure? Please send an email to .
Mis geen nieuwe vacatures!
Meld u nu aan en ontvang de nieuwste Connection vacatures in Utrecht
Het is gratis en je kunt e-mailupdates op elk moment uitschakelen
Ontvang nieuwe vacatures in je mailbox!
Ontvang e-mailupdates voor de nieuwste Connection vacatures in Utrecht
Het is gratis en je kunt e-mailupdates op elk moment uitschakelen