Jobs

On-going positions, various deadlines

The IT University of Copenhagen invites highly motivated individuals to apply for a Postdoc position starting in July 2026 or soon thereafter.

The HCI & Design section is seeking to hire a postdoc on the topic of AI in Care Technologies. The postdoc will work with the design of ethical and purposeful human-AI interactions, drawing on perspectives that emphasize relationality, situated agency, and posthuman approaches to responsible AI. The research would leverage interaction design to question and reframe mainstream AI paradigms, fostering alternative AI futures that prioritize human and more-than human wellbeing, care, and socio-cultural sensitivity. The postdoc will be teaching 40% of their time in the digital design bachelor's and master's programs.

The Department of Computer Science, Machine Learning Section, invites applications for a fully-funded PhD fellowship. The position is part of the Global Wetland Center (GWC), funded by the Novo Nordisk Foundation. The start date is July 01, 2026 or as soon as possible hereafter. The submission deadline is April 06, 2026.

We are looking for a creative student who is interested in contributing to the mission of the GWC, by developing novel machine learning methods to model greenhouse gas fluxes from both remotely sensed multimodal data and ground-level measurements. To overcome challenges of limited reference data, the student will work on hybrid modelling combining process-based models and deep learning, as well as self-supervised learning approaches. The PhD student will contribute to the development of new global scale datasets.

The Department of Electronic Systems at The Technical Faculty of IT and Design invites applications for a postdoc in the field of Physical Artificial Intelligence and its integration with wireless communication and sensing as per May 1, 2026, or as soon as possible thereafter. The position is available for a period of 18 months.
How will the physical AI evolve being exposed to data from various sensors and radio signals? This is the main underlying theme to be explored within this postdoctoral position.

The IT University of Copenhagen invites highly motivated individuals to apply for a Tenure Track Assistant Professor position starting in August 2026 or soon thereafter. 

We are looking for a researcher of game- and play-related technologies to contribute their own research agenda to the highly interdisciplinary research environment of the Center for Digital Play (CDP). The CDP is an interdisciplinary research unit that develops novel theories and methods for the study of play and games in the 21st Century. From game-trained Artificial Intelligence, to social communities created around videogames, gamification, esports, or game engines as artistic tools, digital play is an intrinsic yet understudied phenomenon in digital societies. The CDPs ambition is to define what it means to study play in digital societies from a multidisciplinary perspective, to develop novel methods and theories needed to deal with novel phenomena, and to be a reference center in the present and future of play and game studies. The candidate will be expected to actively participate in Center events, pursue individual or co-authored research, and participate in dissemination activities, funding applications, and innovation initiatives. Applicants should provide a vision document outlining how they wish to contribute to a diverse learning environment and interdisciplinary research efforts surrounding digital play practices.

The position involves equal parts teaching and research. There are opportunities for the development of new courses, especially in the area of Life-long Learning, and participation in more general computer science degree programmes. Initially, the candidate will be expected to teach in the MSc in Games, specifically in its Game Technology track, where they would be responsible for introductory and advanced teaching on games-specific programming (e.g. efficient programming in C++, game engine architecture, real-time computer graphics). Teaching at ITU also covers supervision of individual research projects, including BSc and MSc thesis.

We are looking for a highly motivated and dedicated postdoc for a 2-years project. You will work on a project related to algorithmic fairness in cardiometabolic disease prediction and care at the Copenhagen Health Complexity Center, Department of Public Health, Faculty of Health and Medical Sciences. The successful candidate is expected to start on the 1 August 2026 (or as soon as possible thereafter).

A key aim of this project, which will be the hired postdoc’s responsibility, is the development of novel predictive models using Danish registry-based data that will serve as a proof-of-concept for population-based, AI-driven prediction models of cardiometabolic diseases that are fair and explainable. The postdoc’s main responsibilities include data management, data analysis, as well as manuscript preparation, and communication of research results to the scientific community (via publications, conference presentations, and alternative ways), as well as to relevant stakeholders, within the above-mentioned scope. Both independent and collaborative work are expected. Over the course of the position, a certain amount of teaching/supervision is expected at the undergraduate or graduate levels.

The Centre for Software Technology (CST), part of Maersk McKinney Moller Institute in the Faculty of Engineering at the University of Southern Denmark (SDU), invites applications for a 3-year PhD position. The position is open from May 1, 2026, and the specific start date will be agreed with the successful candidate.

In this project, we aim to investigate the paradigm of explainable AI (i.e. XAI), especially with reference to its interesting facet of commonsense knowledge (CSK). 

Note that there is growing trend towards XAI today. Opaque-box models with deep learning (DL) might potentially offer high accuracy but are not explainable due to which there can be problems in interpretation, trust, error tracing etc. On the other hand, XAI methods offer clear-box models, often comparable to DL in accuracy, yet better in 1st-time scenarios (where the AI has not exactly encountered the given situation with pre-training earlier), as well as in counterbalancing bias & overfitting. 

In addition to classical XAI models, e.g. decision trees, there is the paradigm of commonsense knowledge (CSK), i.e. everyday knowledge on concepts, properties, and relationships. It is easy for humans and often the hardest for AI systems (vs. encyclopedic knowledge). It often involves design of KBs (knowledge bases) with CSK followed by extraction and use in targeted applications. 

This project entails involvement of CSK and other XAI methods in intelligent systems, considering the given application domain.

The Centre for Software Technology (CST), part of Maersk McKinney Moller Institute in the Faculty of Engineering at the University of Southern Denmark (SDU), invites applications for a 3-year PhD position. The position is open from May1 2026 or as soon as possible thereafter, and the specific start date will be agreed with the successful candidate.

In recent years, there is a need for studying and using sustainable AI methods to head towards a green transition. This is particularly important for environmental initiatives to achieve the targeted 2050 climate neutral goals of the EU as well as the United Nations Sustainable Development Goals (UN SDGs). These initiatives are in line with Denmark’s ambitious 2045 climate neutrality target as well. Promising research directions in the initiatives include investigating sustainable machine learning approaches and addressing renewable energy related projects. Likewise, deploying a novel paradigm of KGML (knowledge guided machine learning) can propel further research.  

The IT University of Copenhagen invites highly motivated individuals to apply for an Assistant Professor (Tenure Track) or Associate Professor position starting in September 2026 or soon thereafter.

The positions will be anchored in the Digital Business & Innovation (DBI) section. DBI brings together research on digital technologies, organizational processes, and human actors to address contemporary digitalization challenges in the private and public sectors. The section currently consists of 13 members, including faculty at all career stages, postdoctoral researchers, PhD students, and research support staff. DBI faculty publish in premier IS journals (e.g., JMIS, JAIS, EJIS, JSIS) and in top journals of adjacent disciplines (e.g., Empirical Software Engineering, Organizational Studies).

The DBI section also hosts the BUILD Lab as a hub for research, education, and engagement with practice. ITU comprises nine research sections, and DBI maintains close collaborations across the university, offering a vibrant intellectual environment for interdisciplinary research that connects information systems research to data science, organizational studies, software engineering, and other areas.

We are seeking to recruit a 2-year postdoctoral researcher within Human-Computer Interaction to work on the interdisciplinary project DARES: Data Quality for Responsible AI in Energy Systems funded by NordForsk, led by Professors Irina Shklovski and Laura Watts. The researcher’s duties will be to manage and conduct in-depth qualitative research that explores how organisational actors, such as companies and regulators, understand and sociotechnically construct ‘data quality’ in energy systems, both now and in the green transition future. The postdoc should, ideally, have experience of critical data studies and both qualitative (e.g. interviews or ethnographic methods) and quantitative data analysis. This postdoc is an opportunity to collaborate in an international Nordic project with external partners across science and technology studies, political sociology, computer science, and engineering.

The NERDS (NEtwoRks, Data, and Society) team at the IT University of Copenhagen welcomes applications from aspiring postdocs in the areas of Data Science, Mathematical Modeling, and Network Science with applications to inference, forecasting, and mitigation in future epidemics. Starting in September 2026 or soon thereafter.

The project “InForM: Inference, Forecasting, and Mitigation of Future Epidemics” (InForM) is funded by the Novo Nordisk Foundation. Its goal is to develop and apply data science tools to strengthen epidemic preparedness. To reach this goal, the project seeks to hire two excellent postdocs. One to improve statistical methods used for epidemic forecasting (e.g. methods to sample and summarize ensembles of simulated epidemic trajectories), and another to improve our understanding of the detailed spread of COVID-19 in Denmark during the pandemic (by studying large datasets of COVID-19 phylogenies in combination with Danish registry data.)

The NERDS (NEtwoRks, Data, and Society) team at the IT University of Copenhagen welcomes applications from aspiring PhD students in the areas of Data Science, Mathematical Modeling, and Network Science with applications to inference, forecasting, and mitigation in future epidemics. Starting in September 2026 or soon thereafter.

The project “InForM: Inference, Forecasting, and Mitigation of Future Epidemics” (InForM) is funded by the Novo Nordisk Foundation. Its goal is to develop and apply data science tools to strengthen epidemic preparedness. To reach this goal, the project seeks to hire an excellent PhD student to improve statistical methods used for epidemic forecasting (e.g. methods to sample and summarize ensembles of simulated epidemic trajectories).

The Amelie Stein group is looking for a PhD student in computational analysis and modelling of protein interaction. The PhD student will work together with other members in the Stein group as well as experimentalists in collaborating groups at UCPH and elsewhere, and other modellers in the Rosetta community. The PhD project aims to study the function of disordered proteins by combining coarse-grained molecular dynamics simulations, machine learning and bioinformatics.

The start date is expected to be 15 July 2026, or as soon as possible thereafter.

The PhD position is part of the Proteins in CONTEXT project where we aim to analyse limitations of current models for protein-protein and protein-ligand interactions, and use these insights to develop better models. The overall project combines data curation, benchmarking, and method development with classic and deep learning approaches.

Are you interested in shaping the future of intelligent and secure energy systems where artificial intelligence meets reliable power electronic systems? We are looking for two motivated PhD candidates, as part of the AI:X initiative at Aalborg University, to work at the intersection of AI, security, and embedded systems, contributing to next-generation trustworthy hardware platforms for cyber-physical energy systems.

AI:X is an ambitious initiative at Aalborg University that aims to advance AI research and create real-world impact through interdisciplinary collaboration, and nine labs will be initiated in 2026 with a total of 18 PhD stipends.

The AI:HARDWARE Lab is part of the AI:X initiative with two PhD stipends and is a collaboration between the Department of Electronic Systems, the Technical Faculty of IT & Design and the Department of Energy, the Faculty of Engineering and Science.

One PhD position will be hosted in the Cybersecurity Research Group at the Department of Electronic Systems in Copenhagen, while the other will be hosted in the Sustainable Power Electronics and Electrification Research Group at the Department of Energy in Aalborg.  

Modern energy systems, such as electric vehicle chargers and power grids, are increasingly exposed to cyber attacks that can cause physical damage. AI:HARDWARE uses AI to protect this infrastructure and to design hardware that is secure by design. The lab also develops AI that runs efficiently on small, low-power devices. The goal is energy systems that are smart, secure, and able to protect themselves.

The two stipends are open for appointment from 15 August 2026 or soon hereafter. The duration of the position is three years.

AI:X is an ambitious initiative at Aalborg University that aims to advance AI research and create real-world impact through interdisciplinary collaboration, and nine labs will be initiated in 2026 with a total of 18 PhD stipends.

The AI:HealthData Lab is part of the AI:X initiative with two PhD stipends and is a collaboration between the Data Engineering, Science, and Systems (DESS) research group, Department of Computer Science, the Technical Faculty of IT & Design and the Center for Clinical Data Science (CLINDA) and Center for General Practice (CAM), Department of Clinical Medicine, the Faculty of Medicine.

The two PhD stipends are open for appointment from 15 August 2026 or soon hereafter. The duration of the positions is three years.  

Health records contain a wealth of clinically valuable information, but much of this information, notably patient journal notes, is unstructured, hindering its use, potentially leading to suboptimal care. AI:HealthData Lab investigates AI methods that extract clinically relevant entities, relations and events from health records and organise them into knowledge graphs, supported by  techniques for efficient retrieval and analytics. As a first application, AI:HealthData Lab focuses on generating contextual and trustworthy patient summaries for general practitioners, saving time and improving care.

AI:X is an ambitious initiative at Aalborg University that aims to advance AI research and create real-world impact through interdisciplinary collaboration. In 2026, nine labs will be initiated with a total of 18 PhD stipends.

The AI: Page-Lab, an AI:X initiative, is a collaboration between the Department of Society and Politics, the Faculty of Social Sciences and Humanities and the Department of Computer Science, the Technical Faculty of IT & Design.

We invite applications for two fully funded PhD stipends in the area of Natural Language Processing (NLP), Knowledge Graphs (KGs), and Large Language Models (LLMs) to explore historical text data and cultural heritage collections.

Collections of historical texts are increasingly used to train AI, but, consisting of highly heterogeneous text data, they are difficult to search and analyse. The AI: PAGE Lab develops AI tools that transform historical texts into machine-readable and machine-understandable structured knowledge about the people, places and events described in the texts. This makes it possible to search across sources, discover hidden connections, and explore history in new ways. The goal is to develop workflows and approaches that make cultural heritage data easier to use and to probe their usefulness for historical analysis.

Both stipends are open for appointment from 15 August 2026 or soon thereafter, and the duration of the positions are three years.

Join AI:GENOMIX, a newly established AI:X Labs at Aalborg University and help push the boundaries of how artificial intelligence can reveal the genetic architecture of common human diseases. As a PhD researcher in AI:GENOMIX, you will contribute to next-generation models that rethink polygenic prediction and support the future of precision medicine. AI:X is an ambitious initiative at Aalborg University that aims to advance AI research and create real-world impact through interdisciplinary collaboration.

The initiative currently hosts five AI:X-Labs with a total of 20 PhD students. In 2026, nine additional labs will be established, including AI:GENOMIX, contributing a further 18 PhD stipends and expanding the university’s cross-faculty research in artificial intelligence. AI:GENOMIX is one of these labs and brings together researchers from the Department of Health Science and Technology (Faculty of Medicine) and the Department of Mathematical Sciences (Faculty of Engineering and Science).

The AI:GENOMIX Lab focuses on developing AI methods that capture how genes interact to influence the risk of common diseases. Traditional genetic tools often analyse genetic variants independently, overlooking complex interaction patterns that may carry important biological information. By integrating deep learning, genome-wide simulations, functional genomics, and large-scale biobank data, AI:GENOMIX aims to deliver more accurate and personalised genetic predictions that can support earlier detection, improved disease stratification, and more targeted prevention strategies.

The two stipends are open for appointment from 15 August 2026 or soon hereafter. The duration of the position is three years.

AI:X is an ambitious initiative at Aalborg University that aims to advance AI research and create real-world impact through interdisciplinary collaboration, and nine labs will be initiated in 2026 with a total of 18 PhD stipends.

The AI:INFRA Lab is part of the AI:X initiative with two PhD stipends and is a collaboration between the Department of Materials and Production, the Faculty of Engineering and Science and the Department of Culture and Communication, the Faculty of Social Sciences and Humanities.

AI:INFRA works on using artificial intelligence to build and run important systems like energy, water, and communication in remote communities. These places often have very limited power, internet access, human and technical resources. The lab explores how AI can help communities run better with fewer resources, while still being reliable and fair. The goal is to develop smart technology that uses very little energy but gives real benefits to people.

The two stipends are open for appointment from 15 August 2026 or soon hereafter. Stipend 1 is a position at Aalborg University’s campus in Aalborg, while stipend 2 is a position at the campus in Copenhagen. The duration of both positions is three years.

AI:X is an ambitious initiative at Aalborg University that aims to advance AI research and create real-world impact through interdisciplinary collaboration. Nine labs will be initiated in 2026 with a total of 18 PhD stipends.

The AI:GENE-XPLAIN Lab is part of the AI:X initiative (read more here: link) with two PhD stipends and is a collaboration between the Department of Culture and Communication, the Faculty of Social Sciences and Humanities and the Center for Clinical Data Science (CLINDA), Department of Clinical Medicine, the Faculty of Medicine.

AI:GENE-XPLAIN develops AI tools that predict genetic cancer risk and help explain these risks to people in a clear and safe way. One part of the project builds AI models that can predict the risk of several cancers at once and explain how genes influence that risk. Another part studies how people understand and react to these predictions, so the information supports good decisions without causing unnecessary worry.

The two stipends are open for appointment from 15 August 2026 or soon hereafter. The duration of the position is three years.

Structural Health Monitoring aims at monitoring the health of in-service structural systems for the purpose of their lifetime assessment, a topic of particular interest to expand the lifetime of wind turbines. Despite remarkable progress in structural health monitoring boosted by AI, purely data-driven models have no physical interpretability and poor generalization capabilities. Thus, they are ill-suited for inference about system's health in rapidly changing environment of wind turbines. Although physical laws can be enforced to learn a model whose parameters can be physically interpreted, there may be groups of different parameters producing the same output as the true system parameters, making it almost impossible to uniquely recover the actual ones. 

AI:Wind-Lab aims to develop a set of fundamental AI methods together with their software implementations for interpretable statistical fault prediction and lifetime assessment in the context of Structural Health Monitoring of operating wind turbines.

Two PhD stipends are available for an appointment. 

AI:X is an ambitious initiative at Aalborg University that aims to advance AI research and create real-world impact through interdisciplinary collaboration, and nine labs will be initiated in 2026 with a total of 18 PhD stipends.

The AI:EMBODY Lab is part of the AI:X initiative with two PhD stipends and is a collaboration between the Department of Culture and Communication at the Faculty of Social Sciences and Humanities and the Department of Architecture, Design and Media Technology at the Technical Faculty of IT & Design.

AI:EMBODY focuses on how individuals communicate nonverbally during therapy sessions, utilizing cues like facial expressions, posture, and movements. These signals are crucial for understanding the therapy process but can be difficult to measure. The lab develops AI technology that analyzes video recordings to identify these subtle cues. This advancement helps therapists gain a better understanding of their clients and the psychotherapy process, ultimately improving mental health treatment.

The two stipends are open for appointments from 15 August 2026 or soon hereafter. The duration of the position is three years.

The two PhD candidates in AI:EMBODY lab will collaborate towards the shared goal of understanding the non-verbal communication of client and therapist in a real psychotherapy setting and analyse how the non-verbal communication is linked to good vs. bad outcomes of therapy.

AI:X is an ambitious initiative at Aalborg University that aims to advance AI research and create real-world impact through interdisciplinary collaboration, and nine labs will be initiated in 2026 with a total of 18 PhD stipends. 

The AI:GeoComm Lab is part of the AI:X initiative with two PhD stipends and is a collaboration between the Department of Electronic Systems and the Department of Sustainability and Planning, hosted at the Technical Faculty of IT & Design.

Rain and humidity weaken wireless signals used for satellite internet and navigation. AI:GeoComm turns this problem into a solution by using signal changes to learn about the weather and take appropriate action. By combining AI with physics and real-time data, the project improves weather forecasts and makes communication systems more reliable, which is especially important for Denmark and Greenland.

The two stipends are open for appointment from 15 August 2026 or soon hereafter. The duration of the position is three years.

The AI:GeoComm Lab invites applications for two PhD positions, each contributing to the shared goal of developing advanced AI-enhanced atmospheric sensing and communication reliability. The lab combines multimodal data sources, physical models, and advanced machine learning to create new forecasting and communication tools.

Are you an established researcher in probabilistic machine learning, with a passion for developing robust, trustworthy, and explainable AI methods for applications in science and engineering? Then this professor position might be for you.

We are looking for a new professor to lead research in probabilistic machine learning, with a focus on areas such as deep generative models, Bayesian methods, and uncertainty-calibrated AI. These approaches are crucial for realizing the potential of machine learning in fields like physics, chemistry, and bioinformatics—where practical and reliable methods are needed to drive digitalization forward.

The professor will play a key role in strengthening DTU Compute’s activities in probabilistic machine learning and will help build a strong research community around applied AI. The position involves leading innovative research, engaging in collaboration with academic and industrial partners, and ensuring high-quality teaching and supervision at all levels.

ou are expected to be part of defining the teaching within the core areas of DTU Compute, including courses on probabilistic machine learning and its engineering applications at the BEng, BSc, MSc, and PhD levels. In addition, there will be an obligation in continuous education on advanced machine learning methods and AI. 

The IT University of Copenhagen invites motivated individuals to apply for a Tenure-track Assistant Professor position in Digital Service Systems, starting on 1 October 2026, or soon thereafter.

Digital Service Systems is an interdisciplinary research field focused on the analysis, design, and governance of digitally enabled services. The field examines how value is co-created through configurations of people, technologies, organizations, and institutional arrangements, understood as changing and relational sociotechnical systems.

Research in Digital Service Systems addresses service innovation, transformation, and coordination across public, private, and hybrid organizational contexts. It encompasses perspectives from, for example, service design, human-centered design, computer supported cooperative work, information systems, and science and technology studies. Particular attention is given to how digital technologies shape work practices, organizational processes, and user participation.

The field contributes to addressing current and emerging societal challenges, including digital sustainability, equitable access to services, democratic and responsible digitalization, and the development of resilient and trustworthy public and private service infrastructures.

The candidate is expected to develop a research agenda, publish in relevant international venues, and contribute to externally funded research activities. We welcome candidates whose research contributes to related agendas, including but not limited to:

• Digitalization of organizations and services
• Systems-oriented perspectives on services
• Digital service transformation
• Service design and digital service innovation
• Service ecosystems and service governance
• Societal and sustainability dimensions of digital services
• Health information systems and services
• NGOs and humanitarian service systems

The Novo Nordisk Foundation Quantum Computing Programme (NQCP) at the Niels Bohr Institute, University of Copenhagen, is seeking a Postdoctoral Researcher. You will be a cornerstone of our project (2026–2029) focused on creating digital twins and AI-driven models for solid state quantum devices. The position is placed in the Theory & Simulation and Data teams of NQCP.

We are looking for a quantum systems modelling profile to help drive our efforts in the development of digital twins of quantum devices.

In this role, you will drive the development of a framework for device-specific digital twins, implementing a full-stack modeling framework that translates low-level multiphysics interactions into high-level system-level insights. Your work will be essential to exploring large design spaces, predicting device behavior, and identify optimal parameters without the prohibitive cost of fabricating numerous physical prototypes.

You will work at the interface of AI and photonic-, semiconducting-, and superconducting quantum hardware. Your work will span across materials, sub-component, and system levels modelling to build a powerful feedback loop where experimental results continuously refine the virtual models, while the models guide the next generation of experiments and device designs.

The IT University of Copenhagen invites highly motivated individuals to apply for a PhD or Postdoc position starting 1 September 2026 or soon thereafter. 

LMLM proposes to build Linguistically Motivated Language Models (LMs). This involves adapting both the training regime and the LM architecture to incorporate different linguistic levels. The hypothesis is that this will lead to mitigation of shortcut learning and, in turn, more reliable LMs. The project will start on the lower levels, investigating how internal structures of words can be used in LMs, followed by words and the syntax level. There will be a strong focus on evaluation, incorporating both standard metrics and benchmarks as well as linguistically oriented and compositionality benchmarks.

Applicants are invited for a double degree PhD fellowship/scholarship at Graduate School of Technical Sciences, Aarhus University, Denmark, within the Electrical and Computer Engineering programme. The position is available from 01 September 2026 or later. 

Note that this is a double degree PhD project. Therefore, the employment will be at Aarhus University, but the place of work will be split equally between Aarhus University, Denmark, and Université Libre Bruxelles, Belgium.

This PhD aim to advance novel techniques to scale and simplify data-driven impact assessment processes making them intuitive, powerful, and accessible to end users, by leveraging large language models (LLMs). LLMs are pre-trained on broad data and can be adapted to diverse tasks, from question answering, and summarization, to data wrangling. More specifically, the aim is to provide users with a single-entry point where they define and structure express assessment tasks in a natural way (e.g., text) and interact with data lakes to perform such tasks.

Applicants are invited for a double degree PhD fellowship/scholarship at Graduate School of Technical Sciences, Aarhus University, Denmark, within the Electrical and Computer Engineering programme. The position is available from 01 September 2026 or later. 

Note this is a double degree project. Therefore, the employment will be at INRAE, Clermont Ferrand, France, but at least one year must be spent at Aarhus University, Denmark.

This PhD aim at advancing a fleet of autonomous robots for arable farming. Work is underway to enable the management and supervision of a fleet at the scale of a site (i.e. a farm). This PhD proposes to set up a sharing of robots in an agricultural equipment-sharing cooperative. It will then be a question of managing a fleet of robots which will be maintained (maintenance, repairs...), configured (installation, change, of tools for agricultural tasks), and stored in a warehouse, before being deployed to work on several sites. 

Applicants are invited for a double degree PhD fellowship/scholarship at Graduate School of Technical Sciences, Aarhus University, Denmark, within the Electrical and Computer Engineering programme. The position is available from 01 September 2026 or later.

Note that this is a double degree PhD project. Therefore the employment will be at Aarhus University, but the place of work will be split equally between Aarhus University, Denmark, and Clermont Auverge University, France.

Wireless communication systems are being used in many applications, as they offer a flexible solution for maintaining connectivity between connected devices. This PhD focus on the use of wireless communications in agricultural mobile robots in Precision Farming. The PhD will also tackle the issue of real-time monitoring of the state of the network to explain the quality of data the operator receives. 

We are looking for a motivated, ambitious PhD student to join the Cryptography Group in the Cybersecurity Engineering Section at DTU Compute (Copenhagen region, Denmark).

This 3-year PhD position (starting on 1 September 2026) will focus on secure Multi-Party Computation and Zero-Knowledge Proofs.

You’ll join a growing, collaborative team of cryptographers at DTU, and you’ll get the chance to connect and work with leading researchers in the Copenhagen region and abroad. 

The focus of the PhD project is on advancing the theory and practice of secure Multi-Party Computation (MPC) and Zero-Knowledge (ZK) Proofs. The successful candidate will investigate the formal design and security analysis of MPC protocols and ZK proofs, with a particular emphasis on foundational aspects. The project will also explore efficiency and post-quantum security, aiming to bridge theoretical advances with their relevance to practical applications.

The Department of Mathematics and Computer Science (IMADA) at the University of Southern Denmark (SDU) invites applicants for several positions as Assistant Professor in University Science Education Research, with a particular focus on learning environments, experience and design. All positions contribute to research on how learning environments and experience shape student engagement, learning and study trajectories in STEM education. We invite applications from candidates with disciplinary backgrounds in Mathematics, Computer Science, Biology, Physics, Chemistry, Pharmacy or related fields, as well as Education, Pedagogy, Psychology, Design or Learning Sciences, who wish to develop a strong research profile in STEM education. 

Applicants are not expected to cover all areas described in this posting; depth in one profile area is valued. 

SDU Center for Industrial Software at the Maersk Mc-Kinney Moller Institute, University of Southern Denmark (SDU) is seeking a highly motivated postdoctoral researcher for a two-year position within the VANTAGE project (Vulnerability Assessment aNd Testing Automation for Global Enhancement). 

The VANTAGE project leverages a multi-agent AI architecture with advanced reasoning capabilities (chain-of-thought reasoning) to transform security operations. It integrates autonomous vulnerability assessment and penetration testing (VAPT), AI-based orchestration, and advanced forensic analysis to enhance cybersecurity operations for modern Security Operations Centers (SOCs) and Computer Security Incident Response Teams (CSIRTs).

We are looking for applicants with strong background in the design and development of multi-agent AI systems in the context of cybersecurity operations and also demonstrated ability to conduct high-quality research. The position is funded under the EU DIGITAL-ECCC programme focusing on the deployment of advanced cybersecurity technologies. It involves leading European research institutions, universities, SMEs, and cybersecurity organizations. The successful candidate will join an interdisciplinary research environment and work under the supervision of Professor Sadok Ben Yahia and Assistant Professor Sani Abdullahi while closely collaborating with academic and industrial partners across Europe.

The position is available from May 2026, or as soon as possible thereafter.

The postdoc will develop machine learning for protein engineering, including: (1) investigating how epistatic effects in proteins can be captured by machine learning models; (2) develop machine learning models for protein engineering that are able to optimize additive as well as epistatic effects.
The work will be in collaboration with domain experts who will be working on optimizing an NADPH-dependent enzyme called formate dehydrogenase. Optimizing this enzyme will be a model system used to evaluate the developed methods.
You will join a highly motivated and collaborative team under the supervision of Søren Hauberg, Wouter Boomsma, and Carlos G. Acevedo-Rocha. The research environment favors creative ‘slow thinking’ style research and we emphasize having fun along the way. Our work is consistently published at the top venues of machine learning and protein research.

At the Faculty of Engineering and Science, AAU Energy, a position as Postdoc in AI-augmented process control, is open for appointment from 01 July 2026 or soon hereafter. The duration of the position is two years.

The main task of this postdoc position will dedicate on research and development of advanced process control augmented by some AI techniques, e.g., using reinforcement learning, for offshore industrial produced water treatment processes. The developed methods/solutions should be tested and demonstrated on a globally leading pilot-plant sited at Aalborg University. There are also potentials to be tested at relevant industrial partners’ installations at the late stage of the project. This position is fully supported by a new EUDP project named ARROiW – Advanced Recording for Reduction of Oil-in-Water, which aims to develop advanced online oil-in-water sensing and control technologies applicable for offshore industrial processes. The ARROiW project involves academic partners as Aalborg University, Technical University of Denmark and Copenhagen University, as well as relevant industrial partners.

Join a young research group dedicated to transforming materials discovery from empirical exploration to predictive design. Our research program builds on a synergy of high-throughput virtual screening, generative machine learning (ML) models, and automated reaction exploration to gain insights into complex chemical systems.

As a PhD candidate, you will work on developing synergistic workflows to model dynamic, multi-phase systems. Your primary focus will be to overcome the limitations of current simulation methods by enhancing machine learning interatomic potentials and develop ML approaches to model rare events and complex environments. A key focus will be solving the "chicken-and-egg" problem of sampling: developing algorithms that learn to bias simulations automatically without requiring prior knowledge of the mechanism. You will contribute to open-source software frameworks and develop strategies to guide open-ended explorations systematically toward desired targets. The project involves strong collaborations with domain experts to align your theoretical models with large-scale experimental datasets.

NQCP invites applicants for PhD fellowships in the Algorithms & Applications (A&A) section within this area.

Start date is 1 October 2026 or as soon as possible thereafter during 2026.

We are interested in developing a project plan with prospective candidates to suit their skills and experience. Current priority areas for A&A are:

• Model Hamiltonians for chemical systems
• State preparation techniques
• Schemes for extracting information and observables from quantum computation
• Noise modelling of logical quantum circuits

A project can span one or multiple of these areas.

We are seeking highly motivated and talented applicants for a 1-year postdoctoral position (with the possibility of 1-2 year extension) in the area of efficient foundation model inference.

This is a full-time, fixed-term position for one year, starting on September 1, 2026, or as soon as possible thereafter.
The initial appointment will run until August 31, 2027, or for 12 months from the actual start date. An extension of 1–2 additional years may be offered, subject to satisfactory performance.

The successful candidate will contribute to cutting-edge research on topics including:

• Token compression and adaptive token pruning;
• Distributed and collaborative inference strategies;
• Mixture-of-Experts (MoE) architectures for scalable inference;
• Resource-aware and latency-constrained inference optimization;
• Edge intelligence and on-device foundation model deployment.

Do you have a passion for solid mechanics and software, and do you want to create solutions for the world's green transition? You will be part of a research group which takes a holistic approach to wind turbine blades, integrating all aspects that contribute to their structural integrity, performance, and sustainability.

We seek a Postdoc who can contribute to the development of computationally efficient modelling, data integration, and digital twin technologies within our projects, with a strong emphasis on real‑time prediction and interaction. One of our main projects are ReliaBlade-2 with more info at https://reliablade.dtu.dk/. You will join a cross-disciplinary, international team collaborating on supporting the R&D needs for key industry players in the wind energy industry. 

Are you ready to launch your scientific career by addressing the urgent need of renewable energy integration? At DTU Construct you will break new ground at the absolute forefront of what is possible in the field of energy storage. 

We invite applications for a fully funded PhD position within the fields of Thermal Energy Storage (TES) and Artificial Intelligence at the Department of Civil and Mechanical Engineering, Technical University of Denmark (Thermal Energy Section).

We seek a talented, self-motivated, and collaborative researcher to develop physics-informed AI methods and transform decision-making in the design and operation of next-generation thermal energy storage systems, including latent heat TES and thermochemical TES. 

Your work will advance a paradigm shift in TES system design, modelling, and control by developing adaptive, physics-informed models integrating thermo-fluid dynamics, deep learning neural networks, and experimental data. A key objective is to overcome limitations of traditional thermo-fluid dynamic approaches in design discovery and TES performance evaluation.

The Department of Electronic Systems at The Technical Faculty of IT and Design invites applications for PhD stipends or integrated stipends in the field of Foundation Models for Neural Speech Tracking within the general study programme Electrical and Electronic Engineering. The PhD Stipends are open from August 1, 2026, or soon hereafter, and the integrated PhD stipends are open for appointments from September 1, 2026.

The PhD project falls under Research Track 2: Tracking neural and perceptual attributes.
The research investigates how the brain learns and tracks acoustic patterns over time. It focusses on accurately capturing neural encoding of perceptual statistical properties and uncovering the mechanisms driving auditory recognition. The methods will range from context tree models to large language models that generate embeddings capturing semantic and statistical relationships.

Applicants are invited for a PhD fellowship/scholarship at Graduate School of Technical Sciences, Aarhus University, Denmark, within the Electrical and Computer Engineering programme. The position is available from 15 August 2026 or later. 

This doctoral project will investigate exciting new ways of digitalizing district cooling systems in megacity environments with hot and humid climates through Digital Twins (DT), including system design and installation support, optimized control, system monitoring, and fault detection, with a major emphasis on scientifically sound modelling and prediction, together with rapid replicability so that solutions can be quickly deployed in new districts.

This raises fascinating research challenges that will be addressed as the core activities of the PhD position:

• Investigate information modelling requirements for effective Digital Twinning of district cooling systems that spans from building to district scales i.e. Building Information Modelling (BIM), Geographic Information System (GIS) modelling standards
• Develop effective algorithms that extract and align the right semantic, geometric, and topological information from diverse models and data sources to be used in cooling system Digital Twins
• Develop evidence-based methods for system design and installation support, e.g. injecting configuration faults into BIM models to predict problems with real-world installations
• Towards rapid replicability, exploit and extend the Digital Twins as a Service (DTaaS) platform for creating and deploying cooling system digital twins by creating reusable DT assets tailored to BIM and GIS
• Develop services for online monitoring and prediction of expected demand and anomaly properties, utilising the FMI-supported Maestro framework for co-simulations between adequate digital twin models (DTaaS), and (initially) the statistical model checking engine of UPPAA
• Through DTaaS, develop new methods that orchestrate AI-driven analysis tools and simulators for multi-scale cooling system prediction, optimized control, monitoring and fault detection, in collaboration with AAU and Grundfos

Applicants are invited for a PhD fellowship/scholarship at Graduate School of Technical Sciences, Aarhus University, Denmark, within the Electrical and Computer Engineering programme. The position is available from 01 August 2026 or later. 

Key Research Objectives. The objective of this PhD is to develop a high-performance, low-latency framework for Test-Time Adaptation (TTA). This involves designing autonomous architectures capable of monitoring and maintaining the reliability of unimodal and multimodal foundation models in real-time. Key research pillars include:

• Autonomous Monitoring: Developing mechanisms to detect distribution shifts and quantify model uncertainty across heterogeneous data types.
• On-the-Fly Adaptation: Designing lightweight TTA algorithms that can recalibrate models at the edge under strict latency and computational constraints.
• Efficiency and Reliability: Balancing the trade-offs between adaptation accuracy, energy efficiency, and hard real-time execution.

The successful candidate will join a pioneering research group focusing on the next generation of adaptive AI, with the opportunity to publish at top-tier machine learning and computer vision venues (e.g., NeurIPS, ICML, CVPR) and validate research on state-of-the-art edge computing testbeds.

We are seeking applicants for an 18-months postdoctoral fellowship focusing on the development of an AI-based phenotyping system for high-throughput screening for aphid performances on pea plants. The position is available from the 1st of November 2026 or as soon as possible thereafter.

The aim of the project is to develop an AI-based phenotyping system for high-throughput screening of aphid resistance in plants both in controlled and field conditions. This tool will be used to screen for aphid resistance in a pea germplasm collection by characterizing aphid-traits related to their performances. In the long term, this will contribute to selection for aphid-resistant pea varieties contributing to sustainable organic agriculture in Denmark.

The appointed candidate will work in a highly experienced research environment, spanning basic biology to applied research for industry outcomes. The hosting team is a multidisciplinary group with expertise in applying various quantitative and statistical modelling approaches to biological systems (including crop genetics, host-pathogen interactions, pathogen population genetics, evolutionary biology...). The candidate will work in close collaboration with a specific group (DARSA) specialized in developing and applying remote-sensing tools and innovative open-source machine-learning methods.

You have a background in Graph Theory, strong mathematical competences and would like to advance your career by conducting research in this field and earning a PhD?

The PhD project is in Graph Theory. It focuses on basic mathematical research concerning Structural Digraph Theory and the intersection of Graph Theory and Combinatorial Optimisation.

Your main tasks will consist of conducting research regarding relaxations of Woodall’s Conjecture about directed cuts and dijoins, and further studies regarding properties of related objects and certain classes of digraphs. Additionally, you will be responsible for supporting the research project by computer aided tasks when reasonable and applicable. You will work with nearby colleagues, and with partners in Denmark as well as abroad. You will also be involved in teaching assistant duties at DTU Compute.

Do you want to be involved in the green energy transition? Do you wish to contribute to the development of machine learning methods with real-world impacts on power electronic converters and drives? Are you looking for a career in R&D or academia? We have multiple opportunities for you!

We invite applications for multiple 3-year fully funded PhD positions that will contribute to the development of a new generation of embedded intelligence within grid-connected power converters and variable-frequency motor drives with edge computing and machine learning capabilities.

We offer a multidisciplinary, international, and friendly atmosphere, encouraging creativity, diversity, empathy, and teamwork. You will have a great opportunity to build strong networks with internationally known researchers at DTU and other universities as well as industrial partners.