05 Postdoctoral Fellowship at Utrecht University, Netherlands

The overarching aim of the project is to investigate why and to what extent ethnic, racial, and religious minorities are structurally exposed to discriminatory behaviour in the Dutch labour market. Moreover, the project examines whether and how this continuous exposure to prejudice and discrimination accumulates at the intersection of stigmatised identities and over the life course.

You will play a central role in our research on Himalayan glaciers, with a specific focus on lake-terminating glaciers. Using state-of-the-art modelling, remote sensing techniques, and field measurements, you will investigate the calving behaviour of lake-terminating glaciers and the additional mass loss resulting from proglacial lake formation. You will also assist in a field campaign to the Himalayas, where you will collect essential data on glacier thickness, surface properties, and lake bathymetry, providing critical ground-truthing for the model. By utilising a glacier ice flow model, you will simulate a selected lake-terminating glacier in the Himalayas and validate the results using both in-situ and remote sensing data. This position offers close collaboration with colleagues from the Institute for Marine and Atmospheric research Utrecht 

We are looking for a PhD and a postdoctoral researcher to work within the multi-partner HAICu NWA-ORC project. This vacancy is for the Postdoc position, the PhD position is being advertised simultaneously: PhD Position on Multimedia Analysis in the HAICu Project. There are two research topics tackled in parallel for this project (see description below). Based on the applications, the topics will be assigned at PhD or Postdoc level. Both researchers will collaborate within the project.

This project is implemented by an ambitious consortium including many universities, knowledge institutions, archives, foundations, cultural institutions and business partners in the Netherlands. It aims to use improved access to digital heritage to tutor the Digital Citizen in the use of big data. It brings together AI researchers and Digital Humanities scholars to seek solutions to the problem of inadequate data-mining tools we have, aiming to derive information from the continuous stream of data about the present and the past. This will help citizens and other regular users, heritage curators and journalists who are interested in tapping heritage collections, as well as civic organizations and authorities interested in improving civic participation.

Through desk research, cross-sectoral industry surveys, and in-depth case studies in healthcare, TechConnect explores how human skills and technology interact in real-world contexts. The project develops a systemic framework to address the gap between intended and actual technology use, offering practical guidelines for technology procurement, development, and training. By providing tools to enhance human-tech integration, TechConnect aims to boost productivity and quality employment across industries, promoting a more inclusive workforce where technology supports human potential and equitable skill development.

As a postdoc in the TechConnect project, you will work within a multidisciplinary team of experts and play a key role in delivering innovative research with significant societal impact. In particular, you will be actively involved in the following tasks:

1. Developing a Conceptual Framework: Contribute to the development of a novel framework for Human-Tech Skill Complementarity by conducting an in-depth analysis of interdisciplinary literature, cross-sectoral surveys, and consultations with expert stakeholders, leading to the production of industry landscape reports.
2. Creating a Human-Tech Skill Complementarity Index: Lead in the creation of an index that assesses the interaction between human and technological skills to enhance productivity and job quality. This will involve carrying out observational case studies within the healthcare sector (hospitals), conducting interviews, and mapping organisational systems.
3. Strengthening Human-Tech Skill Complementarity: Contribute to building a predictive model to identify critical factors that drive Human-Tech Skill Complementarity, through interventional case studies, interviews, and collaborative workshops.
4. Driving Industry and Organisational Impact: Support efforts to improve how technologies are designed, developed, and integrated across industries, with the aim of increasing productivity, work quality, and resilience. This includes defining business cases and developing guidelines for multiple sectors and occupational groups.

The position is part of the research funded by European Research Council (ERC) under the ERC-Consolidator grant scheme. You will work in an interdisciplinary team with the PI, 2 PhD researchers from the fields of (experimental) linguistics. There will be another postdoctoral researcher joining the project later.

This project aims to develop, implement and test a general model of memory that can provide insights into how we store and retrieve linguistic information and how our language use is intertwined with memory when we communicate. The model to be developed and tested will be hybrid in the sense that it merges linguistic factors uncovered in computational and theoretical linguistics with general cognitive mechanisms. The overarching goal is to find out how the model of memory can be generalized across various linguistic domains, from the lexicon through syntax to discourse semantics, and how the memory model can help us predict diverse quantitative data in linguistics and cognitive science.

There are two components in the project: an empirical and a computational one. The empirical component of the project consists in developing, carrying out and analysing experiments that collect behavioural data (e.g., reaction times, eye fixations) and EEG data. The computational modelling component involves simulating behavioral and neural data connected to processing and memory retrieval. This postdoc position is part of the computational component of the project.