16 Postdoctoral Fellowship at University of Copenhagen, Denmark

In a context of multiple global crises–COVID-19, increased inequality, and climate change–citizens are looking to political leaders and the state to solve problems and protect them. The increased role of the state might fundamentally change the conditions under which business operates around the world.

This project investigates how business actors manage the regulatory challenge in two of the most pressing structural transformations in the 21st century – the rising inequality and climate change. It poses the following research question: Under what conditions can business be powerful in the high-salience politics of wage inequality and carbon emissions?

Specifically, the postdoctoral researcher will investigate how businesses in Denmark and Germany have historically influenced wage policies and climate regulations through self-regulation, lobbying, and coalition-building.

In a context of multiple global crises–COVID-19, increased inequality, and climate change–citizens are looking to political leaders and the state to solve problems and protect them. The increased role of the state might fundamentally change the conditions under which business operates around the world.

This project investigates how business actors manage the regulatory challenge in two of the most pressing structural transformations in the 21st century – the rising inequality and climate change. It poses the following research question: Under what conditions can business be powerful in the high-salience politics of wage inequality and carbon emissions?

The postdoctoral researcher will be responsible for designing, implementing, and analyzing survey experiments that assess how business self-regulation influences public opinion on wage inequality and carbon emissions regulation.

INNER_LEAGUE is a 5-year ERC Consolidator Project (2025-2030), headed by Haakon A. Ikonomou (PI). INNER_LEAGUE provides a comprehensive social-bureaucratic history of the League of Nations Secretariat. The project will investigate the inner life of the secretariat to (a) understand how it shaped the professional lives of the ca. 4000 people that worked there. And (b) how this global workplace shaped the lasting bureaucratic infrastructures of multilateralism it serviced.

To deliver on its undertaking, the project implements an approach combining social, institutional, and digital history across three work packages: (i) Communities, (ii) Hierarchies, and (iii) Infrastructures.

To operationalize its approach, INNER_LEAGUE has several concrete objectives:

1. To systematically uncover and analyze the emergence, endurance, change and impact of professional, educational, epistemic, social, and emotional communities within the League Secretariat.
2. To examine the often-contested formation of hierarchies within the League Secretariat via state-of-the-art digital approaches.
3. To investigate how processes of community building and hierarchization impacted upon the professional lives of the staff of the League Secretariat.
4. To study and explain how, and under what material circumstances, these hierarchized communities of officials and staff built, maintained, operated, and passed on new infrastructures of multilateralism.

We are looking for candidates with a doctoral-level background in computer science, machine learning, natural language processing, computational humanities or social sciences, computational linguistics, or similar fields who are interested in working collaboratively to apply computational methods to the INNER_LEAGUE Project.

The postdoctoral researcher’s primary role will be to develop and implement NLP methodologies that can aid the team in effectively retrieving, processing, analyzing, and interpreting historical documents. The project draws on the fully available, digitized and OCR-scanned archival material of the League of Nations (c. 15.000.000 pages – in French and English).

Experience in working with the history of international organizations, international public administrations and/or multilateral diplomacy in the 20th (and 21st) century is a plus, but not a requirement. Proficiency in reading English and French is a requirement. 

The morphAI project aims to create the methodological foundation for using modern AI and data science techniques for modeling morphological variation. Part of this is to model non-diffeomorphic variation in a mathematically rigorous way that preserves the geometric foundation for diffeomorphic shape analysis. In the DIGIFABA project, we will adapt infinite-dimensional shape models based on actions of diffeomorphisms to plan shape analysis, allowing statistical analysis of plant shape and e.g. regression analysis on the effect of external variables on the plant growth.

The postdoc project will span between these areas with a common focus on advanced shape models, both in terms of mathematical modeling, actual application, and numerical implementation. Part of this is to bridge between the pure mathematical description of shape and biologically relevant features. The developed shape models need to allow efficient numerical implementations, and numerical implementation is an important part of the work. It is the aim that the implemented models should be available in accessible open-source software packages.

The ideal postdoc will have extensive prior experience in the above fields with particular emphasis on the geometry of shape models. It is important that you find using advanced mathematical tools to solve biological questions interesting. In addition, it is important that the postdoc is ambitious and able to actively collaborate with the other project participants, both on the applied and mathematical sides. Finally, a strong desire to execute and get the work done is necessary. Physical presence at the workplace is expected.

The project is about developing machine learning (ML) methods that help to develop the food of the future. The successful candidate is expected to conduct basic research in ML and to contribute to the application of ML in the food science.

Currently, plant ingredients are often refined to almost molecular purity – and then combined again to create structured foods. This isolation is resource intensive, and the removal of fibre and micronutrients can compromise the nutritional value. This can be mitigated by applying milder forms of processing that do not fully refine ingredients and leave some of the native structure of the plant material intact. These less refined ingredients however exhibit complex behaviour, and we therefore need machine learning to direct the experimental data generation that will be carried out by other team members in the project.

Learning meaningful representation spaces that model the complex space of ingredients and their properties can be immensely useful. These representation spaces can be informed by multiple modalities of data, spanning time-series data, microscopy images, rheological measurements, and so on. Integrating these modalities into common representation spaces can help in the development of more sustainable food. Furthermore, incorporating active learning methods can steer new experimentation while incorporating adequate prior domain knowledge.

The successful candidate will be able to choose one of two projects, depending on their personal interests and skillsets: either (1) investigating how cells recognize and repair DNA damage in mitosis; or (2) CRISPR screening approaches to define how RecQ helicases maintain genome stability to limit premature aging and cancer development.

These projects will benefit from access to cutting-edge mass spectrometry, imaging, screening and computational biology infrastructure at the Department of Cellular and Molecular Medicine. Collaborations are in place locally to access additional facilities and techniques including state-of-the-art optical tweezers, super-resolution microscopy and cryo-electron microscopy.

Your main tasks will be regarding surgery on rodents (primarily rats). In addition, there will be ordering materials, and other practical matters. Transporting animals to and from the lab. Assisting in performing neuroscience experiments. Analyzing data, primarily using videotracking software such as deeplabcut. 

You will be investigating how certain cerebrospinal fluid borne proteins activate nociceptors in the trigeminal ganglion. As a research assistant in the Kaag Rasmussen lab, you will be working with in vivo fluorescent imaging and calcium sensitive fluorophores to explore how cerebrospinal fluid proteins influence neuronal activity in the trigeminal ganglion.

The successful candidate will utilize advanced surgery, in vivo imaging techniques with calcium sensitive fluorophores to characterize nociceptor firing patterns upon application of putative migraine inducing cerebrospinal fluid proteins. This research aims to unravel how cerebrospinal fluid proteins elevated after migraine with aura might drive the migraine phenotype.

You will utilize advanced surgery skills to expose trigeminal ganglia in the skull base. Then with in vivo imaging approaches, you will monitor peripheral nervous system activity in C and A-delta fibers that signal pain information. Then you will monitor the firing patterns before, during and after application of proteins that we have reason to believe alter the firing patterns in the nociceptors. Your tasks will include the design and execution of experimental workflows that integrate real-time imaging, calcium imaging, and analysis of the recordings. Additionally, you will perform behavioral assessments to evaluate the pain phenotype.

We are looking for highly motivated and dynamic young researchers for the position of a Postdoc or Assistant Professor for a period of two years, who can conduct high quality research on topics within responsible Machine. We expect the assistant professor position to start 1 October 2025 or as soon as possible thereafter. The postdoc position is extected to start early 2026.

The postdoc will work approximately one third of the time on the NyMarkModel (primarily in the first year) and two thirds of the time on the PHISHES projects.

The project NyMarkModel aims to to develop an improved N modeling approch that can calculate reliable estimates of N leaching and soil C balance at the field level from farm activity data, especially related to mineral and organic N fertilisation, crop choice and rotation, soil type and climate.  The project is funded by the Danish Ministry of Food, Agriculture and Fisheries and lead by University of Copenhagen with partners from Aarhus University and SEGES Innovation.

The project PHISHES aims to quantitatively assess, through state-of-the-art modelling, how different agricultural management strategies impacts soil pollution, soil processes and functions, ecosystem services and surface water quality at catchment scale. Agricultural management systems studied includes conventional tillage (CT) and conservation agriculture (CA) practices. The project is funded by the EU Horizon Europe Soil Mission program and lead by Danish Hydraulic Institute, with University of Copenhagen and a range of European organisations as partners.

We invite applications for a postdoc position in the field of cardiac fibrosis as per September 1st 2025, or as soon as possible thereafter. The position is a fixed-term full time position ending on Nov 30th 2027.

We are looking for an exceptional candidate with interdisciplinary skills ranging from animal experimentation to in vitro cell culture expertise. It is crucial that the candidate is interested in working in an interdisciplinary environment with partners from both industry and academia.

You will apply histological, molecular and biochemical methods to explore the role of presynaptic proteins in animal models of epilepsy, in cellular models, and in clinical samples. The work is highly translational and will involve a variety of technologies to identify the expression of synaptic vesicle glycoprotein 2A (SV2A) and other synaptic proteins under various conditions. We expect you will be able to design and conduct neurobiological research studies independently and professionally together with junior scientists in the team that you supervise. You will be communicating your results at internal meetings, at conferences and in scientific publications, so communications skills are important in this role. We emphasise personal relationships and collaborations.

The Novo Nordisk Foundation Quantum Computing Programme (NQCP) is establishing a talented and diverse international team to create a cutting-edge quantum programme in the heart of Copenhagen, Denmark. At the Niels Bohr Institute, University of Copenhagen, where the formulation of Quantum Mechanics was born 100 years ago, we aim to establish an international quantum computing programme, funded by the Novo Nordisk Foundation, that will drive research and innovations at multiple levels – from developing scalable quantum processor technologies to solutions for the quantum-classical control and readout interface, and all the way to quantum algorithms and applications.  The long-term mission of the programme is to develop fault-tolerant quantum computing hardware and quantum algorithms that solve life-science-relevant chemical and biological problems.