Postdoctoral Fellowship (06) at Vrije University Amsterdam, Netherlands

The Department of Mathematics of Vrije Universiteit Amsterdam welcomes applications for a two-year Postdoctoral position in Reinforcement Learning for Stochastic Optimization. The candidate is expected to conduct high-quality research at the intersection of reinforcement learning and stochastic optimization. The objective is to contribute to the development of novel methodologies that advance both theoretical understanding and practical application. The postdoc will actively explore how reinforcement learning techniques can be applied across a range of complex operational domains, such as energy systems, health care, and scheduling and planning. A strong interest in interdisciplinary collaboration and the ability to connect with ongoing departmental research efforts are essential. Preference will be given to candidates who can connect to existing research strengths in the department. We are an inclusive, interdisciplinary group, and diversity and internationalism are at the heart of our research principles, as well as our teaching practice.

While we know that human cognition is unparalleled, we lack a mechanistic understanding of the specific neurons and circuits that support it. This PhD project, funded by European Research Consolidator grant focuses on the function of the specialized neuron types in the human cortex that are vulnerable in Alzheimer disease – layer 3 Pyramidal Neurons and Double Bouquet Cells (DBCs). Our previous work shows that human layer 3 Pyramidal Neurons have distinct physiological and morphological properties that distinguish them from other species and link to cognitive scores. These neurons might play a role of a hub in cognitive networks integrating information from thousands of synaptic inputs. To keep this excitation in balance it must be matched by inhibition. Another human specialized interneuron type – Double Bouquet cell – might provide this inhibitory balance. These neuron types are likely to be critical for human cognition as they are selectively lost in cognitive disorders. In this project you will investigate how these neurons function and form circuits in the human brain, and how their activity translates to more efficient computation. 

We are looking for a PostDoc who will do research on the intersection of machine learning (ML) and statistics. The focus will be on enriching statistical methods through advanced machine learning techniques, for instance, by learning latent representations of the data. In addition to utilizing such techniques for predictive modeling scenarios, causal modeling is also within the scope of the position. The position is embedded in the ten-year gravitation grant Stress in Action, funded through NWO (Dutch National Science Foundation). The goal of the project is to move stress research from the lab into daily life, and hence, the use cases of methodological innovations will focus on applications to stress-related data, such as wearables, ecological momentary assessments, and other types of questionnaires. A variety of academic partners are involved in the project, including Vrije Universiteit Amsterdam, Amsterdam UMC, Erasmus MC, University of Twente, University of Groningen, UMC Groningen, and Utrecht University. The position is embedded in the Quantitative Data Analytics (QDA) group of the VU in close collaboration with Erasmus MC and the University of Groningen. The QDA group focuses on both fundamental and application-driven research in ML. We are looking for candidates with experience in the area of machine learning or statistics, with a special preference for those with expertise in one or more of the following areas: representation learning, causal inference. We are interested in attracting a PostDoc who is able to perform ground-breaking research on fundamental aspects of machine learning and statistics and wants to apply these innovations in the context of the Stress in Action project. 

Due to ageing, the impact of vision threatening diseases such as diabetic retinopathy (DR) and age-related macular degeneration (AMD) on the health care system will only increase.

In this project we will develop techniques to quantitatively assess the oxygen saturation status of the retinal microvasculature. Reduced blood oxygen levels may lead to hypoxia, which is one of the key drivers of the formation of new blood vessels. These new blood vessels are often leaky, which leads to complications such as vision loss and, ultimately, to blindness. The development of techniques to detect the onset of retinal hypoxia will thus allow timely therapeutic interventions that will prevent vision loss.

In this project, in which VU, TNO and Heidelberg Engineering collaborate, we will develop a multi-color scanning laser ophthalmoscope (mcSLO)-based oximeter with retro-illumination capabilities. The retro-mode mcSLO will be a versatile research tool that provides freedom in the selection of imaging wavelengths and allows different implementations of light delivery and collection to and from the retina. We will develop novel image analysis algorithms for retro-mode imaging to quantify the wavelength-dependent scattering and absorption properties of the retina, from which the microvascular oxygen saturation can be calculated. The image analysis algorithms will be partly based on Monte Carlo simulations of light transport in the retina. The performance of the system and algorithms will be validated on model eyes with controlled scattering and absorption properties.

The Department of Finance seeks to appoint a postdoctoral researcher in empirical banking, with a focus on credit supply and bank risk. The position is funded through an internal faculty incentive grant and is offered for a fixed period of one year.

The postdoctoral researcher is expected to initiate and develop an empirical study in banking during the appointment. Depending on the project and mutual interest, short research visits to external institutions, including central banks, may be possible.

This position is intended for candidates who have recently completed, or expect to complete, their PhD and wish to further develop their research agenda during a focused one-year postdoctoral appointment.

This two-year postdoctoral position is part of the VIDI research project “Emotion-Infused Risk Regulation: Rethinking the Fundamentals of Regulatory Governance for Citizen-Centric Rulemaking”, funded by the Dutch Research Council (NWO) and led by Dr. Dovilė Rimkutė.

The VIDI project investigates the role of emotions in regulatory governance, examining how emotions shape both regulators’ formulation of rules and citizens’ reception of regulatory responses. It is structured around three interlinked objectives: (1) Emotion and Regulatory Responsiveness: To what extent and why do regulators respond to citizens’ emotion-laden concerns? (2) Citizens’ Emotional Responses in Regulatory Encounters: To what extent and how are citizens’ emotions elicited during interactions with regulators? (3) Emotions and Regulatory Legitimacy: What are the effects of citizens’ emotions on their perceptions of regulators’ legitimacy? Read more about this research agenda in the following link: Affective regulatory governance: towards an emotion-based understanding of citizen-regulator interactions in regulatory politics.

The postdoctoral project will contribute to the emerging research agenda on affective regulatory governance, with a particular focus on citizens’ emotions in the Regulatory State context (Objectives 2 and 3). Specifically, the project will examine emotionality in citizens’ interactions with the regulatory state and experimentally test causal effects and mechanisms through which emotions influence citizens’ perceptions of regulators’ legitimacy.