University of Copenhagen, Denmark invites online Application for number of Fully Funded PhD Degree at various Departments. We are providing a list of Fully Funded PhD Programs available at University of Copenhagen, Denmark.
Eligible candidate may Apply as soon as possible.
(01) PhD Degree – Fully Funded
PhD position summary/title: PhD scholarship in Grundtvig Studies at the Faculty of Theology
WWD investigates how the influential Danish theologian, thinker, and poet N.F.S. Grundtvig worked with textual sources from antiquity to his own day. In addition to the analysis of Grundtvig’s published works, the project group will take advantage of a new research infrastructure called Grundtvig’s Manuscripts Online (GMO). GMO uses the AI-software Transkribus to transcribe of more than 80,000 unprinted pages in the Grundtvig Archive at the Royal Danish Library. The shared theoretical foundations for the interdisciplinary research team are Modern Genre Studies and Conceptual History.
Deadline : 22-06-2026
(02) PhD Degree – Fully Funded
PhD position summary/title: PhD fellowship in Biochemistry and Structural Biology
We are looking for a driven and ambitious candidate with the ability to work independently and in collaboration with other groups. The candidate should have a strong interest in persuing a PhD in the field of protein science with a focus on protein assembly.
The project will address fundamental questions regarding the structure and fuction of polymerizing enzymes. The goal is to define the rules that govern the homo- and hetero-oligomeric assembly of key enzymes from intermediary metabolism and includes using a range of biochemical and biophysical techniques, including enzyme assays, polymerization assays, and cryo-electron microscopy.
Deadline : 3rd June 2026
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(03) PhD Degree – Fully Funded
PhD position summary/title: PhD fellowship in Machine Learning for Crystallography
This fellowship forms part of the Novo Nordisk Foundation-funded project ‘Deep Learning-Accelerated Crystallography Pipeline’, a collaboration between University of Copenhagen, Durham University, and the MAX IV synchrotron. You will work closely with an international team of crystallographers, mathematicians, and data scientists. The project seeks to transform small-molecule structure determination by integrating machine learning algorithms into crystallographic workflows. The successful candidate will contribute to the development of computational tools that will enhance data collection, refinement and validation.
The work will involve simulation of diffraction data, training and testing machine learning models, and integration into an open-source modular pipeline for high-throughput crystallography.
Deadline : 3 June 2026
(04) PhD Degree – Fully Funded
PhD position summary/title: PhD fellowship in sustainable fertiliser management and greenhouse gas mitigation
Nitrous oxide is an important greenhouse gas. About 70% of the N2O emissions comes from agricultural fields as a consequence of nitrogen fertilization. The N2O is produced during nitrification and denitrification following the application of mineral and organic fertilizers. Management strategies should aim to limit microbial N transformations before plant uptake. SNIs have been proposed as an effective measure to reduce N2O emissions, with studies showing average reductions of 40–50%, along with a comparable decrease in nitrate (NO3⁻) leaching.
The overall objective of this project is to quantify N2O emissions and NO3⁻ leaching from synthetic and organic fertilizers applied to major crops, such as winter wheat and spring barley, and to assess the effectiveness of SNIs in mitigating these nitrogen losses.
Deadline : 1 June 2026
(05) PhD Degree – Fully Funded
PhD position summary/title: PhD fellowship in Mechanistic Interpretability for LLM Security
The position is offered in the context of the project “A Mechanistic Framework for Mitigating the Susceptibility of LLMs to Learning False Information” funded by Independent Research Foundation Denmark, led by Isabelle Augenstein and Pepa Atanasova. The project goal’s will be to develop a novel theoretical frameworks for LLM security, new mechanistic interpretability methods, and new evaluation protocols, developed through research at the intersection of Natural Language Processing, LLM Security, and Explainable AI. The PhD student’s research is expected to focus on researching mechanistic interpretability methods to curb the effects of false information attacks on LLMs at different stages of the model lifecycle. In addition to the PIs and the PhD student, the team also includes a postdoctoral researcher, as well as the opportunity to apply as an academic collaborator with NVIDIA as part of an existing relationship.
Deadline : 31 May 2026
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(06) PhD Degree – Fully Funded
PhD position summary/title: Fully funded PhD position on images and justice
The PhD will be part of the ERC Consolidator Grant, Before the Image – The Political Ontology of Images for Legal and Social Justice. The project will investigate how images used to document violence, war crimes and human rights violations are created – not only in the moment when they are taken or viewed, but also in processes of designing image technologies and developing camera and visual literacy skills.
As part of this larger project, the PhD will investigate how visual literacy, including memory, perceptions of truth, and training, impact ways in which images are seen, focusing on how experts and non-experts view images that document violence. It is expected that the PhD candidate will carry out ethnographic fieldwork at open source investigation trainings and do interviews with trainers and participants at these trainings in order to study the processes through which open source investigators are taught to view images for the purposes of verification, geo- and chronolocation etc.
Deadline : May 27, 2026
(07) PhD Degree – Fully Funded
PhD position summary/title: Two PhD fellowships in Astrophysics and Planetary Science
The PhD projects focus on the origin of chemical complexity in star- and planet-forming regions, building on data from large observing programs utilising the Atacama Large Millimeter/submillimeter Array (ALMA) and James Webb Space Telescope (JWST). The overarching scientific question is to what degree the chemistry of complex organic molecules depends on the conditions of the natal environment of the young stars and their subsequent evolution. Through the projects, we aim to understand what role, if any, the chemical complexity plays in the emergence of planetary system.
Project 1 will the primarily focus on analysis of data from the ALMA Large Program, Complex Organic Molecules in Protostars with ALMA Spectral Surveys (COMPASS). The PhD candidate will use these ALMA data to identify complex organic species in the warm regions close to young stars, with the goal of accurately characterising the molecular composition of gas at the stage of planet formation.
Project 2 will primarily focus on observations of interstellar ices using the James Webb Space Telescope. The PhD candidate will measure the concentrations of such ices across star-forming clouds and relate them to the physical structures of the clouds, as constrained by large scale gas-phase maps. In this way, the project will reveal the initial conditions for protostellar chemistry.
We anticipate that the two PhD students will work closely together, exploiting synergies between the two projects as well as with other ongoing efforts within our group on numerical and simulations and radiative transfer calculations of star and planet formation.
Deadline : 27 May 2026
(08) PhD Degree – Fully Funded
PhD position summary/title: Two PhD fellowships in Astrophysics and Planetary Science
The Niels Bohr Institute/Astrophysics and Planetary Science section invites applicants for two PhD fellowships in the chemistry of planet formation. The project is part of the Villum Young Investigator project “Chemistry meets Astrophysics: pathways to life-enabling ingredients during planet formation”.
Project 1
The PhD project 1 will investigate how the chemical composition of planet-forming disks shapes the volatile inventories of planets. Recent observations with the James Webb Space Telescope (JWST) have revealed a surprising diversity in the chemistry of inner disks, including systems that appear depleted in water but enriched in hydrocarbons. The project will combine infrared spectroscopic observations from JWST with data from the Atacama Large (sub-)Millimeter Array (ALMA) to characterize the chemical composition and physical structure of disks around very low-mass objects. These observations will be complemented by numerical simulations to put firm constraints on the physical and chemical processes responsible for the observed diversity. The project will help establish how variations in disk chemistry influence the building blocks of planets.
Start date is (expected to be) 01.09.2026 or as soon as possible thereafter.
Project 2
The PhD project 2 will focus on characterizing the solid budget of planet-forming disks, including both ices and refractory materials. The student will analyze infrared spectroscopic observations obtained with the James Webb Space Telescope (JWST), targeting a sample of protoplanetary disks. Spectral decomposition will be carried out using state-of-the-art fitting routines in combination with laboratory ice spectra, and the analysis will be complemented by radiative transfer modeling to derive ice column densities. By characterizing disk ices across a statistically significant sample, the project aims to reveal the chemical composition of the solid building blocks available for planet formation.
Deadline : 26 May 2026
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(09) PhD Degree – Fully Funded
PhD position summary/title: PhD fellowship in Biotechnology
The PhD fellowship is part of a larger project aimed at developing novel fungicides to combat human pathogens. This specific project will focus on the use of new AI-based models for protein design. In particular, protein binders will be developed to target the fungal proton pump Pma1. The goal is to design, screen, identify, and characterize new protein binders capable of killing the fungal pathogen Candida albicans, without impacting vitality of human cells
The project is one of several in the lab working on designed protein binders and will therefore benefit greatly from already established workflows and protocols.
The project is carried out in collaboration with Mark Gresnigt (Group Leader at the Leibniz Institute for Natural Product Research and Infection Biology), whose lab has advanced microscopy setups for monitoring Candida albicans infection in human cell systems. Successful protein binders will be tested using these setups during a research exchange stay in his lab.
Deadline : 25 May 2026
(10) PhD Degree – Fully Funded
PhD position summary/title: 1-2 PhD fellowship(s) in Human-computer Interaction
The distinctive potential of Virtual reality (VR) is to give people experiences of being in worlds they otherwise could not be in, having a body that is unlike their real one, and doing things they could not do in real life. That potential can be realised with VR interaction techniques that map physical movements to virtual ones. Yet, their development is largely based on designers’ intuition.
In MOVR, we will start from the assumption that the use of such VR interaction techniques requires motor learning. We will investigate how models and paradigms from motor learning literature can inform systematic approaches to design and evaluate VR interaction techniques. The intended impact is to provide HCI research a scientific foundation to shift the development of VR interaction techniques from a craft to science.
Deadline : 22 May 2026
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(11) PhD Degree – Fully Funded
PhD position summary/title: 1-2 Postdocs in Human-computer Interaction
The distinctive potential of Virtual reality (VR) is to give people experiences of being in worlds they otherwise could not be in, having a body that is unlike their real one, and doing things they could not do in real life. That potential can be realised with VR interaction techniques that map physical movements to virtual ones. Yet, their development is largely based on designers’ intuition.
In MOVR, we will start from the assumption that the use of such VR interaction techniques requires motor learning. We will investigate how models and paradigms from motor learning literature can inform systematic approaches to design and evaluate VR interaction techniques. The intended impact is to provide HCI research a scientific foundation to shift the development of VR interaction techniques from a craft to science.
Deadline : 22 May 2026
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(12) PhD Degree – Fully Funded
PhD position summary/title: PhD fellowships in RNA interference in plants
We use genetic, biochemical and transcriptomic approaches to understand both mechanistic aspects of post-transcriptional genetic control and its biological functions. The PhD projects advertised here focus on two distinct aspects of the use of RNA interference systems to detect and defend against foreign genetic code. One project investigates the role of RNA-dependent RNA polymerases in classical RNA interference; the other project investigates how variant RNA interference pathways can be employed to activate innate immunity pathways through cytoplasmic immune receptors.
Deadline : May 22, 2026
(13) PhD Degree – Fully Funded
PhD position summary/title: 2 PhD fellowships in Machine Learning for Biology and Drug design
PhD1: Project in tractable, neuro-symbolic foundations for biomolecular machine learning.
The PhD project is part of TRANSFORMBIO, a collaboration between the BioML group at the University of Copenhagen (PI: Wouter Boomsma) and the University of Edinburgh (Co-PI: Antonio Vergari), focused on developing tractable neurosymbolic AI for biological sequence modeling.
The core challenge is that current foundation models for biology – despite their impressive performance – lack the ability to perform reliable, flexible probabilistic inference. They cannot exactly evaluate arbitrary conditional distributions or guarantee that predictions conform to known biological constraints. The PhD student will work on two main problems. First, developing probabilistic circuits (PCs) as expressive and tractable alternatives to variational autoencoders for protein family modeling, enabling flexible conditioning on observed amino acids and exact likelihood computation while maintaining competitive predictive performance. Second, developing scalable methods for constrained decoding in biological sequence models, ensuring outputs always respect structural or grammatical biological constraints such as codon-length rules or transmembrane topology. The position offers a collaborative international environment, including a research stay in Edinburgh.
PhD2: Project in Literature-Aware Neuro-symbolic Modeling of GPCR Interactions. The PhD project is a collaboration between the BioML group at the Department of Computer Science (PI: Wouter Boomsma) and the Pharmaceutical Informatics group at the Department of Drug Design and Pharmacology (Co-PI: Alexander Hauser), focused on developing a neurosymbolic AI framework that integrates biomedical literature with 3D molecular structure for interpretable reasoning about protein–ligand interactions. The core challenge is that current AI systems treat scientific text and molecular geometry as separate knowledge sources: large language models process literature without grounding statements in 3D structure, while structure-based models ignore the mechanistic insight present in scientific text. This project bridges that gap, with a focus on G protein-coupled receptors (GPCRs) – a pharmacologically important protein family with a rich structural and ligand literature. The PhD student will work on extracting and jointly representing biochemical and geometric knowledge from the GPCR literature, designing a neurosymbolic architecture based on probabilistic circuits that combines natural-language evidence with molecular geometry, and validating the resulting model on GPCR binder rediscovery tasks – with the longer-term goal of proposing novel binders. The PhD is part of a cohort of PhD students in the Center for Pharmaceutical Data Science Education (CPDSE), providing the PhD student with a uniquely interdisciplinary environment spanning AI methodology and pharmaceutical sciences.
Deadline : 21 May 2026
(14) PhD Degree – Fully Funded
PhD position summary/title: PhD Project in AI for Analytical Chemistry
We are seeking a motivated PhD student to work on deep learning methods for automated detection and identification of small molecules from chromatography and mass spectrometry data. The project combines self-supervised segmentation models for signal detection in chemical data with probabilistic generative models for de novo molecular structure prediction from mass spectra, with emphasis on uncertainty quantification in low-annotation regimes. The segmentation component focuses on learning to detect chemical signals across diverse instrument platforms directly from unlabeled data, without relying on manual parameter tuning. The generative modeling direction treats structure elucidation as a conditional generation problem over a vast chemical space, where the key challenge is not only accuracy but producing calibrated uncertainty estimates when labeled spectrum-structure pairs are scarce. Both directions involve methodological contributions to deep learning in semi-supervised and self-supervised representation learning, grounded in a high-impact application domain.
The work is motivated by pressing non-target screening problems in environmental water analysis and is carried out in close collaboration with analytical chemistry experts at the University of Copenhagen. This gives the project direct access to large-scale experimental datasets from wastewater and drinking water monitoring and provides real-world evaluations.
Deadline : 20 May 2026
(15) PhD Degree – Fully Funded
PhD position summary/title: PhD fellowship in Stem Cell Biology at the Department of Drug Design and Pharmacology
We are looking for an outstanding and passionate scientist who has a strong background in human pluripotent stem cell biology. This PhD project aims at exploring approaches to revert changes in lipid metabolism associated with genetic risk factors for Parkinson’s Disease in induced pluripotent stem cell derived dopaminergic neurons. Your task will involve knocking down / out genes encoding for specific enzymes in lipid metabolism and to assess its effect on lipid and pathological protein levels in healthy and Parkinson’s Disease patient’s neuronal cells. The stem cells from the healthy controls and patients with Parkinson’s Disease are available and banked in our laboratory.
The project is funded by a Novo Nordisk Ascending Investigator grant and involves an established collaboration with the laboratory of Agnete Kirkeby (ReNew, Copenhagen) and Kristine Freude (Department of Veterinary and Animal Sciences, Copenhagen).
Deadline : 20 May 2026
(16) PhD Degree – Fully Funded
PhD position summary/title: PhD Scholarships: Geopolitical Struggles of the Emerging Global Tech Order
The University of Copenhagen hereby invites applications for one or more PhD scholarships at the Department of Political Science. The successful candidate will work on the project “TECHORDER: Geopolitical Struggles of the Emerging Global Tech Order,” funded by the European Research Council led by Professor Rebecca Adler-Nissen. The successful candidate will be enrolled in the Copenhagen Graduate School of Social Sciences at the Faculty of Social Sciences.
TECHORDER explores the emerging “global tech order” – the ideas, power structures and rules that shape digital technology and the relationships between governments and major tech companies (big tech). The project focuses on the ideas of leaders and employees at big tech firms as well as government officials from countries such as the US, China, India, the UK, France, and Germany, an in organizations such as the EU, UN and OECD as well as more specialized organizations. TECHORDER investigates how these actors view two key technologies: artificial intelligence and quantum technology, their own organizations’ roles, and the global power dynamics involved in setting global and regional tech rules. Using a multi-method approach – including ethnographic research, participatory mapping, surveys, interviews, computer vision, and network analysis – the project aims to uncover the hidden cultures, geopolitical rivalries and governance efforts that are reshaping the idea of international order in the digital age.
Deadline : 18 May 2026
(17) PhD Degree – Fully Funded
PhD position summary/title: PhD Fellowships in measurement-induced quantum phase transitions
The Quantum Matter Lab at the Niels Bohr Institute, University of Copenhagen, invites applicants for PhD fellowships to investigate measurement-induced quantum phase transitions in epitaxial semiconductor-superconductor hybrid materials.
Candidates should have a Master’s degree, preferably with experience in experimental condensed matter physics, mesoscopic electron transport, or experimental solid-state quantum information science. The project combines nanofabrication, low-temperature measurements using a cryofree dilution refrigerator, low-noise and high-frequency electrical measurement techniques, data analysis, and close collaboration with theoretical physicists. Scientific writing and communication will be in English. The role involves close collaboration with our partner, the University of Washington, and may include extended scientific exchange visits to their laboratories. The position may also include the performance of other duties.
Deadline : 17 May 2026
(18) PhD Degree – Fully Funded
PhD position summary/title: PhD positions in AI in Medicine
Funding for two PhD positions working on the use of AI in medicine is available. The positions are focused on various aspects of cancer treatment, including AI-assisted diagnosis, treatment planning, and outcome prediction. Depending on the applicant’s qualifications, they may work on medical image analysis, clinical report analysis, or theoretical aspects of AI in medicine. The researchers are expected to work in close collaboration with the Department of Radiation Oncology and the Department of Radiology at Rigshospitalet.
The prevalence of cancer remains a global health challenge, with the National Institutes of Health reporting that an estimated 39.5% of individuals will have cancer at some point in their lives. According to the European Society for Radiotherapy and Oncology, approximately half of cancer patients will require radiotherapy (RT) as part of their treatment regimen. However, the curative effects of RT are accompanied by toxicity risks to healthy tissues surrounding the target tumors. Studies indicate that 15–45% of patients across different cancer types experience various radiation-induced toxicities. This project aims to leverage AI capabilities to study the relationships between toxicities and irradiation of anatomical subregions of human organs, pinpointing critical regions that need to be spared to minimize toxicity risks.
These positions are intended for candidates interested in advancing AI in medicine, with a primary focus on medical image analysis. The research spans multimodal data integration, combining imaging with clinical and treatment-related information. While the main application area is cancer diagnosis and treatment planning, the work also includes related domains such as modelling clinician behaviour (e.g., eye-tracking analysis) and methodological development in medical image analysis. The latter is designed to produce broadly applicable techniques that extend beyond specific tasks and contribute to general advances in AI for healthcare. We are looking for committed candidates who are not afraid to ask questions, can navigate a dynamic research environment, and can independently drive a project until models are applied.
Deadline : 17 May 2026
(19) PhD Degree – Fully Funded
PhD position summary/title: Marie Curie PhD fellowship in stem cell biology at the Department of Drug Design and Pharmacology Faculty of Health and Medical Sciences
The selected PhD candidate will participate in the EU-funded HORIZON-MSCA-DN-2024-01 project LipAgg. The LipAgg network brings together partners from five European countries and comprises nine academic institutions and twelve industrial partners. The consortium is committed to delivering an outstanding training programme for fifteen doctoral candidates aimed at elucidating the role of lipids in the toxicity and propagation of protein aggregation.
The Doctoral candidate key tasks will be to manage and carry out the assigned research project, participate in the LipAgg training and network activities, take PhD courses, write scientific articles and your PhD thesis, participate in national and international congresses and scientific meetings, undertake a research stay at an external research laboratory within the LipAgg network, and disseminate the obtained scientific results.
In particular, the doctoral candidate enrolled in this position, will investigate the cellular toxicity of amyloid-protein-lipid (AP-L) complexes in pancreatic cells and iPSC-derived neuronal cells. The cellular toxicity of the AP-L will be compared to that of lipid-free AP complexes. The influence of AP-L inhibitors on cell toxicity will also be investigated.
The Doctoral Candidate will be enrolled at University of Copenhagen under the supervision of Associate Professor Céline Galvagnion. The project includes a 7-month secondment at Uppsala University under the supervision of Professor Anna Erlandsson, as well as a 1-month secondment in Lundbeck.
Deadline : 17 May 2026,
(20) PhD Degree – Fully Funded
PhD position summary/title: Marie Curie PhD fellowship in protein and lipid biophysics at the Department of Drug Design and Pharmacology
Our research aims at understanding the role of dysfunctions in lipid homeostasis in the emergence of neurodegenerative diseases including Alzheimer’s and Parkinson’s Diseases. Our approach consists in identifying, using biological models, lipid changes associated with these diseases and/or their risk factors and in using biophysical methods to provide at the molecular level the mechanism by which these lipid changes can influence functional protein-membrane interactions and protein aggregation. The different biological models that we consider vary in their complexity and include patient derived cells and brain materials. Our interdisciplinary research involves an international collaborative network including neuroscientists, stem cell biologists, biochemists, protein biophysicists and experts in lipidomics and proteomics.
The main methods/techniques that we routinely use in the laboratory include molecular biology, recombinant protein production/purification; characterisation of protein, protein-membrane interactions and self/co-assembly using circular dichroism, fluorescence spectroscopy, calorimetry, electron microscopy; lipids extraction and characterisation using mass spectrometry; cell culture (established and iPS cell lines), Immunocytochemistry, Western Blot, qPCR; organelle and ex-vivo material isolation.
Deadline : 17 May 2026,
(21) PhD Degree – Fully Funded
PhD position summary/title: Marie Curie PhD fellowship in stem cell biology at the Department of Drug Design and Pharmacology
The selected PhD candidate will participate in the EU-funded HORIZON-MSCA-DN-2024-01 project LipAgg. The LipAgg network brings together partners from five European countries and comprises nine academic institutions and twelve industrial partners. The consortium is committed to delivering an outstanding training programme for fifteen doctoral candidates aimed at elucidating the role of lipids in the toxicity and propagation of protein aggregation.
The Doctoral candidate key tasks will be to manage and carry out the assigned research project, participate in the LipAgg training and network activities, take PhD courses, write scientific articles and your PhD thesis, participate in national and international congresses and scientific meetings, undertake a research stay at an external research laboratory within the LipAgg network, and disseminate the obtained scientific results.
In particular, the doctoral candidate enrolled in this position will investigate whether amyloid-protein-lipid (AP-L) complex may seed the aggregation of endogenous IAPP, αS and Aβ in their relevant cells (pancreatic cells, iPSC-derived neuronal cells). The propensity for the AP-L complexes to trigger aggregation in cells will be compared to that of lipid-free AP assemblies. Finally, the potential inhibitory effect of small molecules and peptidomimetics on in cellulo protein aggregation will also be investigated.
Deadline : 17 May 2026,
About The University of Copenhagen, Denmark – Official Website
The University of Copenhagen is a public research university in Copenhagen, Denmark. Founded in 1479, the University of Copenhagen is the second-oldest university in Scandinavia, and ranks as one of the top universities in the Nordic countries and Europe.
Its establishment sanctioned by Pope Sixtus IV, the University of Copenhagen was founded by Christian I of Denmark as a Catholic teaching institution with a predominantly theological focus. In 1537, it was re-established by King Christian III as part of the Lutheran Reformation. Up until the 18th century, the university was primarily concerned with educating clergymen. Through various reforms in the 18th and 19th century, the University of Copenhagen was transformed into a modern, secular university, with science and the humanities replacing theology as the main subjects studied and taught.
The University of Copenhagen consists of six different faculties, with teaching taking place in its four distinct campuses, all situated in Copenhagen. The university operates 36 different departments and 122 separate research centres in Copenhagen, as well as a number of museums and botanical gardens in and outside the Danish capital. The University of Copenhagen also owns and operates multiple research stations around Denmark, with two additional ones located in Greenland. Additionally, The Faculty of Health and Medical Sciences and the public hospitals of the Capital and Zealand Region of Denmark constitute the conglomerate Copenhagen University Hospital.
A number of prominent scientific theories and schools of thought are namesakes of the University of Copenhagen. The famous Copenhagen Interpretation of quantum mechanics was conceived at the Niels Bohr Institute, which is part of the university. The Department of Political Science birthed the Copenhage
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