PhD Candidate on Decoding Value Structures through Computational Exploration

Are you passionate about investigating fundamental research questions in computer science, information and/or systems theory, and natural/artificial forms of intelligence? Are you intrigued by the idea of understanding both social and artificial systems and enhancing their interconnected influence? This project aims to investigate methods and computational models to improve our understanding of values embedded in social systems, to guide socio-technical interventions. The PhD candidate position is embedded within the Socially Intelligent Artificial Systems (SIAS) group of the Informatics Institute of the UvA.

What are you going to do?

In AI research and development, system evaluation is typically guided by a single core question: Does this solution outperform its alternatives? Yet, critical AI discourse makes clear that there is a prior question that needs to be answered: What does this solution work for? As computational systems become deeply intertwined in global socio-technical ecosystems, having a better understanding of the network of distributed expectations, perceptions, and transformations of value(s) revealed through social interactions is an essential basis for addressing adequate interventions. From a computational perspective, this "reverse engineering" pursuit can be supported by several lines of research. Two alternative directions can be investigated through this PhD position, which are outlined below (as a candidate, please select and elaborate on one of these directions in your research statement).

Direction 1: Value structures discovery on simulated social systems. To what extent can contemporary computational methods help us to identify the inner functioning of distributed socio-technical systems? Constructs issued from agent-based modelling, complex adaptive systems, multi-agent and normative systems literature allow us to create increasingly sophisticated informational, motivational, and governance mechanisms. These models can mirror established socio-economic models, drawn for instance from historical reconstructions or model-based theoretical frameworks, and can be executed to generate synthetic data. Data-driven computational techniques can then be applied for the detection of various value translations inherent to or emerging from the underlying socio-economic model. These techniques may rely on approaches currently developed in AI (eg. causal discovery, reinforcement learning, explainable AI methods), in computer science (eg. model construction through compression), or in computational science (eg. neural differential equations, Markov's blankets). Limitations observed in this benchmark will be instrumental in proposing methods tailored to the reverse engineering task.

Direction 2: Processing user narratives for value ascriptions. How can human experiences be leveraged as primary source of knowledge to investigate the behaviour of systems? Narratives play a primary role in constructing and securing the mechanisms of intentionality, both at individual and collective level; various contributions in cognitive science argue that they provide the highest level of integration of an individual’s knowledge system. Contemporary natural language processing (NLP) techniques may provide instruments to automatically extract insights from narratives of people detailing individual interactions with eg. a device, a service, an organization. By disentangling these micro-level scenarios in an adequate representational model, we may construct a broader qualitative behavioural model of the system. This artefact can serve as a platform for investigations, both with respect to the real system in itself (eg. for stress testing), and to involve people further (eg. to test expectations on scenarios not yet accounted, or to frame requests for other past experiences). This approach becomes particularly relevant when data or models are not available to direct inspections, and provides a more systematic role to socially-distributed "anecdotal evidence" for computational research and development, in analogy to the use of case studies in medicine.

This PhD project will be conducted at the Socially Intelligent Artificial Systems group, under the supervision of Giovanni Sileno, within the theme People, Society and Technology of the Informatics Institute at the Science Faculty of the University of Amsterdam.

Tasks and responsibilities:

• Explore several types of methods proposed in the literature (AI, computer science, information studies, …), for value discovery and/or narrative processing;
• Develop new methods and computational models, informed by relevant theories developed in the humanities (linguistics, cognitive and/or social studies, economics, law, …);
• Work independently in a highly multidisciplinary and international environment;
• Regularly present internally on your progress;
• Regularly present intermediate research at peer-reviewed international conferences and workshops, publish them in proceedings and journals;
• Assist in relevant teaching activities;
• Complete and defend a PhD thesis within the official appointment duration of four years.

What do you have to offer?

Your experience and profile:

• MSc degree in Computer Science, Artificial Intelligence, Computational Social Science, Information studies, (Applied) Mathematics/Physics, or related fields;
• A strong background and qualifications in computational modelling;
• Excellent programming skills;
• Socially engaged, highly motivated to understand social dynamics;
• Strong communication, presentation and writing skills, and excellent command of English;
• You are highly motivated, independent, and creative. You are a keen analyst, are open-minded, and have a strong interest/curiosity towards theories developed in other fields.

Experience in performing interdisciplinary research, and studies in the humanities, economics, and/or ecological systems are considered a plus.

Our offer

A temporary contract for 38 hours per week for the duration of 4 years (the initial contract will be for a period of 18 months and after satisfactory evaluation it will be extended for a total duration of 4 years). The preferred starting date is to be discussed. This should lead to a dissertation (PhD thesis). We will draft an educational plan that includes attendance of courses and (international) meetings. We also expect you to assist in teaching undergraduates and master students.

The gross monthly salary, based on 38 hours per week and dependent on relevant experience, ranges between € 2,770 in the first year to € 3,539 in the last year (scale P). UvA additionally offers an extensive package of secondary benefits, including 8% holiday allowance and a year-end bonus of 8.3%. The UFO profile PhD Candidate is applicable. A favourable tax agreement, the ‘30% ruling’, may apply to non-Dutch applicants. The Collective Labour Agreement of Universities of the Netherlands is applicable.

Besides the salary and a vibrant and challenging environment at Science Park we offer you multiple fringe benefits:

• 232 holiday hours per year (based on fulltime) and extra holidays between Christmas and 1 January;
• Multiple courses to follow from our Teaching and Learning Centre;
• A complete educational program for PhD students;
• Multiple courses on topics such as leadership for academic staff;
• Multiple courses on topics such as time management, handling stress and an online learning platform with 100+ different courses;
• 7 weeks birth leave (partner leave) with 100% salary;
• Partly paid parental leave;
• The possibility to set up a workplace at home;
• A pension at ABP for which UvA pays two third part of the contribution;
• The possibility to follow courses to learn Dutch;
• Help with housing for a studio or small apartment when you’re moving from abroad.

Are you curious to read more about our extensive package of secondary employment benefits, take a look here .

About us

The University of Amsterdam (UvA) is the Netherlands' largest university, offering the widest range of academic programmes. At the UvA, 42,000 students, 6,000 staff members and 3,000 PhD candidates study and work in a diverse range of fields, connected by a culture of curiosity.

The Faculty of Science (FNWI) has a student body of around 8,000, as well as 1,800 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 mission of the Informatics Institute (IvI) is to perform curiosity-driven and use-inspired fundamental research in Computer Science. The main research themes are Artificial Intelligence, Computational Science and Systems and Network Engineering. Our research involves complex information systems at large, with a focus on collaborative, data driven, computational and intelligent systems, all with a strong interactive component.

The Socially Intelligent Artificial Systems research group (SIAS) studies how to advance people's everyday life and society in general through AI research, education and impact. The group engages in incremental trust building  and value learning with stakeholders  across various scientific disciplines and application domains, and on topics that are relevant both socially and academically.

Want to know more about our organisation? Read more about working at the University of Amsterdam.

Any questions?

Do you have any questions or do you require additional information? Please contact:

Job application

If you feel the profile fits you, and you are interested in the job, we look forward to receiving your application. You can apply online via the button below. We accept applications until and including 31 January 2024.

Applications should include the following information (all files apart from your CV should be submitted in one single pdf file ):

• A detailed CV including the months (not just years) when referring to your education and work experience;
• A letter of motivation (max. one page) and a research statement (choose one of the two directions outlined above, explain why you would choose it and what approach you would take to it, max. 2 pages);
• A list of publications, if applicable;
• The names, affiliations, and email addresses of three academic referees who can provide details about your academic profile in relation to this position (please do not include any reference letters in your application).

Please make sure to provide ALL requested documents mentioned above.
You can use the CV field to upload your resume as a separate pdf document. Use the Cover Letter field to upload the other requested documents, including the motivation letter and reserach statement, as one single pdf file .

A knowledge security check may be part of the selection procedure.
(for details: National knowledge security guidelines ).

Only complete applications received within the response period via the link below will be considered. Please don’t send any applications by email.

We will invite potential candidates for interviews soon after the expiration of the vacancy.

The UvA is an equal-opportunity employer. We prioritize diversity and are committed to creating an inclusive environment for everyone. We value a spirit of enquiry and perseverance, provide the space to keep asking questions, and promote a culture of curiosity and creativity.

If you encounter Error GBB451/ GBC451, please try using a VPN connection when outside of the European Union. Please reach out directly to our HR Department  directly. They will gladly help you continue your application.

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