09 PhD Degree-Fully Funded at Vrije University Amsterdam, Netherlands

This fully funded four-year PhD position is part of the NWO-M 2024 research project “Real Fake: How Highly Immersive Disinformation Affects What People Believe”. The project investigates how people respond to immersive disinformation: highly realistic, AI-generated content such as deepfakes and 360° virtual reality videos. By looking and feeling authentic, this kind of content can make people feel as they are truly witnessing an event. Whereas most disinformation research focuses on text, we assume that highly lifelike digital (mis)experiences of immersive disinformation can shape beliefs more powerfully by creating a sense of “being there”.

The project: Financial institutions are obliged to perform tasks related to financial economic crime (FEC) such as anti-money laundering, sanctions evasion and terrorism financing. These are crucially important yet challenging tasks. First, they require considerable resources (e.g., costs, employees, IT infrastructure, specialized training). Second, they may require the use of quantitative models, data analysis, and algorithms, but these applications must also safeguard the data privacy and non-discrimination rights of their clients. This topic will become even more relevant in the current age with the dawn of AI.

Your project will be a part of the ORC-NWA consortium project “De-escalating Aggressive Encounters between Frontline Workers and Citizens.” The aim is to understand the mechanisms that drive escalation and de-escalation of aggressive encounters between frontline workers and citizens. The project involves academic and societal partners working together. We are looking for three PhD’s for the project to analyze video recorded encounters between citizens and different types of frontline workers: PhD1 on law enforcement, PhD2 on public transport and PhD3 on service work. These multimethod projects involve participant observations, and both qualitative and quantitative analysis of video footage.

We are seeking candidates who are interested in learning or already have experiences with video analysis, have an affiliation with observational and statistical methods, and are passionate about working in an interdisciplinary team.

Are you a public administration or management student interested in AI and/or value-based governance? Are you interested in doing research about the risks of AI use in public administration and how to manage conflicting public values? Please apply at Vrije Universiteit Amsterdam VU!

As a PhD candidate (0.8-1.0 FTE) you are part of the NWO-funded project “AI4ALL: Value-aligned AI for Public Organizations”. You conduct research on the actual and intended use of AI in public organizations, researching the intended reasons and expected impact of AI in the public sector, and empirically measuring public values affected by the use of AI in public governance. More specifically, your research will focus on empirically measuring public values affected by AI use in public governance, examining which values are actually impacted and what citizens consider most important in terms of value trade-offs. The research methods include document analysis, interviews with various stakeholders, including affected citizens, and a citizen survey among the Dutch general public.

Our theory group is a worldwide leader in studying the statistical physics of living systems, ranging from chromosomes to migrating cells and multicellular tissues. We aim to understand the emergent functional dynamics and organization of living systems in close collaboration with various experimental labs. We currently have an opening for a fully funded 4-year PhD position.

We are looking for highly motivated applicants for a PhD student to strengthen our research team in an interactive and collaborative environment.

You will join an ambitious research project at the Vrije Universiteit Amsterdam (VU), carried out in close collaboration with ARCNL. Our research focuses on computational imaging for biomedical applications. By combining advanced numerical methods with customized optical imaging systems, we aim to enhance resolution, boost imaging speed, reduce costs, and introduce innovative contrast mechanisms.

This project aims to push the boundaries of optical coherence tomography (OCT) by breaking current acquisition speed records by an order of magnitude. To achieve this, we will employ full-field swept-source OCT, combined with sparse sampling and compressive sensing.

As a PhD candidate, you will play a key role in the experimental realization, characterization, and application of this cutting-edge imaging approach. You will also collaborate closely with another PhD student at ARCNL, working on complementary aspects of the project.