The Informatics Institute is seeking a PhD candidate for a computational network science position to work on an exciting research project in an interdisciplinary team. You will focus on the use of mathematical and computational methods to understand social and financial processes in crime and their interplay.

There is a growing consensus that the complexities underlying crimes and criminal organisations cannot be unravelled by traditional methods alone. A shift in research paradigm to complex adaptive systems and network thinking is therefore imperative to move this field forward. This type of expertise in the crime field is still limited, however. To build this expertise we take up the challenge of computational modelling of criminal networks and value chains. These systems are a complex interplay between social networks, trust, opportunity, and financial activities. A system’s approach that encompasses the complexity of these pathways can support analysts and investigators in effectively tackling undermining criminal activities in a strategic manner.

Particularly novel to this project is that multiple rich intelligence datasets (anonymised) will be combined in order to create large and multiplex networks (social and financial) surrounding criminal activities. This quantitative data will be combined with qualitative knowledge from domain experts. The data will be conceptualised as a snapshot of a dynamical system which is adaptive and decentralised. The goal is to model the process of formation and evolution of the network and value chains therein, as well as to understand the function of the emergent network topology as an infrastructure for information, money, and commodities.

What are you going to do?

You will focus on identifying and modelling the dynamics of adaptation to different intervention strategies by law enforcement. Criminal networks are infamous for their resilience against different intervention strategies. Interventions can be aimed at central actors, but also on actors with a specific role within a value chain. Each criminal activity, such as cocaine trafficking, money laundering or migrant smuggling, has its own value chain. For example, illegal cannabis cultivation involves property owners, electricians, cutters, distributers, and sellers, each with specific skill sets and dependence on each other. Read further about the subject in this article*.

The first goal is to understand the adaptation processes after different types of interventions based on historic police data. Second, is to integrate these insights into a model for adaptation that can be used to simulate the different effects of interventions, such as centrality attack, value chain attack, etc. Third, we aim to use the knowledge of adaptation processes and value chains to predict potentially missing links from the inherently incomplete data sets, by matching partial value chains and inferring highly likely unobserved links which would complete the value chain.

*Duijn, Paul AC, Victor Kashirin, and Peter MA Sloot. 'The relative ineffectiveness of criminal network disruption.' Scientific reports 4 (2014): 4238.

The ideal candidate for this position:

• has a M.Sc. in Applied Mathematics, Complex Systems Science, Computational Science, Statistical Physics, or related disciplines, with experience in programming language(s) such as Python;
• has an affinity towards and good knowledge of network science (graph theory). Preferably has experience in computational modelling of networks, network processes, network flow dynamics, and/or calculating various network topological features;
• is familiar with the concept of value chains and has an affinity towards understanding the dynamics of criminal value chains which are embedded in social, financial, and trust networks;
• enjoys interacting with domain experts from different disciplines and tackling an interdisciplinary problem by internalising and subsequently integrating qualitative knowledge into computational models or quantitative analyses;
• iIs trained in computational modelling and simulation techniques, such as Monte Carlo sampling;
• has strong knowledge of the Dutch language in reading and speech, since most data and metadata is in Dutch and may contain Dutch slang.

Fixed-term contract: Four years.

A temporary contract for 38 hours per week for the duration of 4 years and should lead to a dissertation (PhD thesis). The initial appointment will be for a period of 18 months and after satisfactory evaluation it will be extended for a total duration of 4 years. You will get a customised Training and Supervision Plan, that will be evaluated every year. We also expect you to assist in teaching undergraduates and master students.

The salary, depending on relevant experience before the beginning of the employment contract, will be €2,325 to €2,972 (scale P) gross per month, based on 38 hours a week. These amounts are exclusive 8% holiday allowance and 8,3% end-of-year bonus. A favorable tax agreement, the ‘30% ruling’, may apply to non-Dutch applicants. The Collective Labour Agreement of Dutch Universities applies.

Are you curious about our extensive package of secondary employment benefits? Then find out more about working at the Faculty of Science.

University of Amsterdam

With over 5,000 employees, 30,000 students and a budget of more than 600 million euros, the University of Amsterdam (UvA) is an intellectual hub within the Netherlands. Teaching and research at the UvA are conducted within seven faculties: Humanities, Social and Behavioural Sciences, Economics and Business, Law, Science, Medicine and Dentistry. Housed on four city campuses in or near the heart of Amsterdam, where disciplines come together and interact, the faculties have close links with thousands of researchers and hundreds of institutions at home and abroad.  

The UvA’s students and employees are independent thinkers, competent rebels who dare to question dogmas and aren’t satisfied with easy answers and standard solutions. To work at the UvA is to work in an independent, creative, innovative and international climate characterised by an open atmosphere and a genuine engagement with the city of Amsterdam and society.

Faculty of Science – Institute for Logic, Language and Computation

The Faculty of Science has a student body of around 6,500, as well as 1,600 members of staff working in education, research or support services. Researchers and students at the Faculty of Science are fascinated by every aspect of how the world works, be it elementary particles, the birth of the universe or the functioning of the brain.

The Computational Science Lab (CSL) at the Informatics Institute tries to understand how information is processed in natural settings through the study of a large variety of dynamic multi-scale complex systems. The project is linked to the 'Networks of Crime and Terrorism' at the Institute for Advanced Study (IAS) of the University of Amsterdam. You will join an interdisciplinary team, consisting of researchers from the Computational Science Lab (CSL), the Regional Information and Expertise Center (RIEC) in Amsterdam, the police, and the Fiscal Information and Investigation Service (FIOD).