16 Postdoctoral Fellowship at Utrecht University, Netherlands

As a PhD candidate you will be working on a subproject within the Consolidator Grant project COOPERATION (2024-2029) funded by the European Research Council (ERC) and directed by Dr Ozan Ozavci   (Principal Investigator, PI) at the Department of History and Art History. COOPERATION project will recapture the lost archives and historical knowledge of international public health cooperation between the ‘global north’ and the ‘global south’ by analysing its first and longest-lasting instances: the sanitary councils in the Middle East and North Africa (MENA). Established in Tangier, Alexandria, Tunis, Istanbul and Tehran, these unprecedented institutions strategised against waves of epidemics and pandemics between the 1790s and the 1940s. Their European, American and native co-founders invented new models for fighting pandemics from below and stopping the diseases in their tracks. They continually strove to overcome the familiar barriers to cooperation posed by inter-imperial competition in a multipolar world, economic inequities, protests against quarantine restrictions and racial and Orientalist biases, among others. COOPERATION project will write an entangled history of health cooperation, by shifting the focus from top-down to bottom-up processes. Consulting archival sources in Europe, MENA, and North America, it will determine the historical preconditions for effective international public health cooperation.

Current projections show that the incidence of diseases on crops will increase in the coming decades, and thus, new strategies, beyond strengthening the immune system, are needed to ensure the resilience of future crops to diseases. It turns out that plants slow down their growth during and after an immune response regardless of the disease intensity. However, how these growth processes are regulated in plants is unclear. In this PhD project embedded in CropXR, you uncover the genetic and molecular basis of plant growth during and after an immune response. With this knowledge, we aim to develop solutions for resistance that do not compromise crop growth.

Current projections show that the incidence of diseases on crops will increase in the coming decades, and thus, conceptually new strategies, beyond strengthening the immune system, are needed to ensure the resilience of future crops. It turns out that plants slow down their growth during and after an immune response regardless of the disease intensity. However, how these growth processes are regulated in plants is unclear. In this curiosity-driven PhD project, you will uncover the genetic and molecular basis of plant growth during and after an immune response. With this knowledge, one could develop approaches that reduce this tradeoff in crop growth. You will primarily work with lettuce (Lactuca sativa), but conservation of the deduced concepts can be investigated in other plant species, such as Arabidopsis thaliana.

The Copernicus Institute of Sustainable Development at Utrecht University has opened two, fully funded, four-year PhD research positions to join the cutting-edge research project ‘Planetary Stewardship in view of Earth-Space Sustainability’ (PLANETSTEWARDS). This research project is led by Assistant Prof. Xiao-Shan Yap, and funded for five years (2024-2029) through a 1.5 million euro ‘Starting Grant’ from the European Research Council (ERC).

Activities in outer space have grown exponentially in recent years, led by an increasing variety of actors from technologically advanced states to billionaire companies and small ventures. While space-based infrastructures such as satellites are essential for basic operations on Earth, space technologies are also presented as the frontier of opportunities and solutions for addressing sustainability crises: global accessibility to the Internet with thousands of satellites, giant solar power stations in Earth’s orbit, resources near and on the Moon, and billionaires’ vision of building space settlements such as on Mars to prevent the extinction of human species. These developments impact sustainability on Earth and in space in various ways. Not only are there rising concerns over space congestion and debris in Earth’s orbit, technological and resource competition on other celestial bodies can cause environmental degradation on those objects, intensify political polarization, fragment sustainability narratives, and perpetuate global inequality. The relations between Earth and space sustainability problems have, therefore, become more intertwined than ever. The fundamental values, beliefs, and institutions that guide stewardship for sustainability require a paradigmatic shift towards simultaneously caring for Earth and space.

The ageing of societies is one of the 21st century’s most disruptive demographic trends. Simultaneously, age-related technologies challenge the ‘naturalness’ of ageing and draw into focus ambiguities in the concept of ageing itself. For instance, technologically-mediated relationships, life extension, and technologies such as AI avatars may make biological and chronological age less relevant, and shift the emphasis to socio-cultural conceptions of age. Such shifts have normative significance particularly if ageing is envisaged as a process that occurs throughout the lifespan.

Since ageing is a phenomenon infused with normativity, with normative expectations corresponding to phases in the human life cycle, the conceptual cleavage of ageing invites innovation in related moral concepts. This PhD project examines ways in which technologies that bear on ageing disrupt biological, socio-cultural, and normative understandings of ageing. It considers how these disruptions generate fruitful possibilities for reconceptualisation of ageing itself, as well as intertwined normative ideas of personhood, meaning, and vulnerability. In doing so, the project will investigate non-western and non-canonical ideas that might reinvigorate core moral concepts implicated by ageing.

This PhD project is an ethical and philosophical study of how technology might (re)shape communal practices and the concepts to describe such practices, notably the concept of solidarity. ‘Solidarity’ plays a fundamental role in many social practices, ranging from political activism to the norms underpinning the welfare state. Over recent years, solidarity has also (re-)emerged as a central concept in moral and political philosophy. Solidarity relations are typically connected to shared social roles: individuals are in solidarity as democratic citizens, workers, those subject to oppression and domination etc.

Disruptive technologies have the potential to deeply reshape these shared experiences and identities that matter for solidarity relationships. Think of genomic technologies in health care practices or artificial intelligence and big data in the (gig) economy. Will such changes to our practices fundamentally alter our understanding of social and political solidarity? On what basis might we conclude that communal concepts like solidarity or community are disrupted? And in what ways could technological change provide new avenues for solidarity bonds and social mobilisation?

This position is one of three PhD positions involved in the research programme. Each PhD researcher will work on its own line of research and will collaborate with the other PhD researchers, the rest of the research team and stakeholders in the living lab. All three PhDs within the PFAS Living Lab will contribute to making this a vibrant, impactful and interactive community. Would you like to contribute to developing sustainable solutions for removing and destroying PFAS substances, remediating this field? 

In this PhD position you aim to advance our understanding of microbial tolerance to, and potential degradation of, PFAS chemicals. Using this knowledge, you will explore the extent to which microbial approaches may help in the development of integrated decontamination approaches in the field.

The Amazon is an important ecosystem for carbon and water cycling. Because of climate change, the Amazon is in transition: experiencing more frequent droughts and taking up less carbon from the atmosphere. Monitoring the Amazon is challenging because of the relatively few local measurements, but through remote sensing we can observe the forest in great detail.

In the department of Earth Sciences we’re seeking a motivated PhD candidate to work on column experiments and numerical modeling of PFAS transport and desorption behaviour in soil. The goal is to understand and quantify the role of drainage systems by combining transport modeling of PFAS in unsaturated soils in the presence of a drainage system with column flushing experiments using field samples. Finally, results and procedures will be adapted for field scale application.

In the position of PhD candidate, you are responsible for conducting research studies (including design, data collection, and data analysis) and publishing about the findings. You will present your findings at national and international conferences, and you will be part of the Postgraduate School for Experimental Psychopathology. You will get to chance to be embedded within a broad international network, including experts in experimental psychopathology, psychometrics and computational psychiatry. The supervisory team for the PhD project comprises Dr Geert-Jan Will, Dr Sanne Bruijniks, Professor Iris Engelhard, and Professor Jaap Denissen. You will be a member of Utrecht’s Experimental Psychopathology lab 

As a PhD candidate you will be working on a subproject within the Consolidator Grant project EcoViolence (2024–2029) funded by the European Research Council (ERC) and directed by Dr Susanne C. Knittel 

EcoViolence is an interdisciplinary, transnational, and comparative study of the cultural imaginary of environmental violence. The project’s aim is to understand how contemporary culture frames and remembers environmental degradation as violence; how it can make visible the deep historical roots that tie eco-violence to other histories of violence, especially colonialism and genocide; and how it articulates and reflects on questions of guilt, responsibility, and implication. EcoViolence will bring together research in cultural memory studies and ecocriticism in order to develop an innovative ecological model for the study of violence, its memory and representation. Furthermore, the project explores how these representations harness affect and emotion to promote critical self-reflection. The project focuses on narrative and visual media and takes a comparative, multilingual, and media-specific approach.

We are working at the interface of biochemistry, molecular biology and biophysics to follow the journey of nascent proteins toward their functional structures as they emerge from the ribosome. These mechanistic studies pave the way for targeted interventions against protein misfolding and perturbed protein homeostasis which are important for a number of aging-related diseases, including neurodegeneration, and several forms of cancer.

, which just relocated from Johns Hopkins University to Utrecht, has established single-molecule optical tweezers assays for probing nascent protein folding on the ribosome. These studies have shown how the ribosome and molecular chaperones counter misfolding and help large, multi-domain proteins attain their functional structures. The group is now combining mechanical manipulation with single-molecule fluorescence detection. These in vitro studies are complemented by cellular assays. Collectively, the work is revealing fundamental principles of cellular protein biogenesis.

The department of Methodology and Statistics

 has a job opening for a PhD candidate. In this position, you will develop novel statistical algorithms to treat missing data in large, longitudinal datasets. Doing so will require you to develop a broad base of statistical expertise and a diverse data analytic toolkit. You will work with Bayesian modelling, (longitudinal) structural equation modelling, high-dimensional prediction algorithms, and computational statistics/numerical methods. You will also have the opportunity to learn high-performance statistical computing techniques and develop highly marketable software development skills. Just for good measure, we’ll throw in four years of intensive on-the-job training in open-science workflows and open-source software development. Are you up for the challenge?

Today’s researchers are blessed with a wealth of high-quality, publicly available, longitudinal datasets. Yet, these data are nearly always incomplete, so fully realising the potential of these rich datasets requires principled missing data treatments. Multiple imputation (MI) is one of the most flexible and broadly applicable principled missing data treatments available. Treating missing data with MI can produce optimal results if the assumptions of the underlying predictive models are satisfied. However, the task of satisfying these assumptions in datasets with hundreds of variables linked by complex, multivariate relations—like the datasets implied above—remains a daunting challenge.

The rapidly evolving field of AI offers promising solutions to the literature screening challenge using machine learning models, like active learning, and, very recently, large language models (LLMs). However, many of these AI-driven solutions emerge from tech companies that publish new models at an unprecedented rate. The rapidity of advancements in the field of AI outpaces meticulous scientific evaluations, leaving many methods unrefined and unproven. The challenge is twofold: keeping pace with these relentless innovations while collaboratively forging a comprehensive understanding of their strengths and limitations.

In the evolving landscape of AI-aided systematic tools (like ASReview , we need to explore which AI model can best be used for which type of data. For instance, while the active learning model (ALM) can facilitate literature screening by presenting the most likely relevant record, the human still needs to make the final labeling decision. In contrast, an LLM can directly generate such labels with explanations, without human input. This project envisions a collaborative approach that leverages the strengths of both humans and different artificial intelligence solutions in systematic screening.