PhD opportunity in AI-driven digital twin modeling for energy systems at Aarhus University

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 May 2026 or later. You can submit your application via the link under 'how to apply'.

Title:
PhD position on AI-driven Multiscale System Modelling for IoE Digital Twin

Research area and project description:
The global push for clean energy and decarbonization has brought unprecedented complexity to modern power systems. The rapid integration of renewable energy sources (RES), the proliferation of smart devices, and the need for reliable and resilient energy infrastructure have given rise to the Internet-of-Energy (IoE)–-a dynamic, decentralized ecosystem of interconnected energy assets. However, traditional modelling and simulation tools fall short in capturing the real-time, nonlinear, and multiscale behavior of such systems. To support intelligent decision-making and efficient energy management in this evolving landscape, there is an urgent need for advanced digital twin technologies that offer accurate, real-time, scalable, and interpretable representations of IoE dynamics. This PhD project addresses this critical challenge.

We are inviting applications for a PhD position within the Marie Sklodowska-Curie Doctoral Network "SAILING," focused on AI-driven multiscale system modelling for the Internet-of-Energy (IoE). This doctoral project aims to develop novel methodologies for building high-fidelity digital twins of complex and dynamic energy systems, enabling real-time simulation and analysis.

The core of this PhD project involves:
1. Developing first-principle modelling techniques to accurately simulate the nonlinear dynamics of IoE devices.
2. Designing a graph neural network (GNN)-based modelling framework to represent the intricate interdependencies among IoE components.
3. Integrating the above into a unified IoE digital twin, capable of multiscale system representation across device and network levels.
This research will be closely aligned with other sub-projects in the SAILING network. While the student’s focus will remain on multiscale system modelling, they will collaborate with other Early-Stage Researchers (ESRs) working on complementary topics, including:

• Low-latency data transmission and fusion.
• AI-based uncertainty analysis and knowledge graph integration.
• Data importance sampling for efficient model execution.
  

Outcomes:

• A novel methodology for multiscale modelling of IoE systems.
• A prototype of an IoE digital twin combining device-level and network-level models.
• Contributions to a broader system framework supporting secure, intelligent energy management.
  

Salary, holiday payment, pension contributions and the like include all employer and employee's taxes and contributions. Thus, figures are before taxes are paid, and taxes may differ depending on individual circumstances. Salary and terms of employment are in accordance with applicable collective agreement, and salary is depending on seniority. Salary includes a non-pensionable PhD supplement. The allowances mentioned in the EU work programme (living allowance, mobility allowance and, if applicable, family allowance) will be part of the salary. Allowance rates can be found in the relevant EU Work Programme (under MSCA doctoral network - Applicable unit contributions), and country correction coefficient can be found in the same document.

Project description: For technical reasons, you must upload a project description. Please simply copy the project description above and upload it as a PDF in the application.

Qualifications and specific competences:
Applicants to the PhD position must have a Master’s degree (120 ECTS) in Computer Science, Computer Engineering, or a closely related field.
In addition, candidates are expected to demonstrate:

• Strong mathematical foundations and programming skills (e.g., Python).
• Background in distribution message passing systems and computation (e.g., MQTT or RabbitMQ)
• Experience in system modelling, numerical simulation, or complex systems.
  

Preferred Qualifications:

• Background in machine learning, graph-based models, uncertainty quantification
• Interest or experience in energy systems, IoT, or digital twin platforms.
• Familiarity with simulation tools, AI libraries, or modelling frameworks.
  

Place of employment and place of work:
The place of employment is Aarhus University, and the place of work is Department of Electrical and Computer Engineering, Helsingforsgade 10, 8200 Aarhus N, Denmark.

EU eligibility requirements in Marie Curie Doctoral Networks:

• Supported researchers must be doctoral candidates, i.e. not already in possession of a doctoral degree at the date of the recruitment. Researchers who have successfully defended their doctoral thesis but who have not yet formally been awarded the doctoral degree will not be considered eligible.
• Researchers supported must be enrolled in a doctoral programme leading to the award of a doctoral degree in at least one EU Member State or Horizon Europe Associated Country, and for Joint Doctorates in at least two.
• Recruited researchers can be of any nationality and must comply with the following mobility rule: they must not have resided or carried out their main activity (work, studies, etc.) in the country of the recruiting beneficiary for more than 12 months in the 36 months immediately before their recruitment date.
• Compulsory national service, short stays such as holidays and time spent by the researcher as part of a procedure for obtaining refugee status under the Geneva Convention75 are not taken into account.
• Secondments are eligible for up to one third of the actual months spent implementing the research training activities under the action.
• In case of industrial doctorates, doctoral candidates must spend at least 50% of their fellowship duration in the non-academic sector.
  

Contacts:
Applicants seeking further information regarding the PhD position are invited to contact:

• Professor Peter Gorm Larsen, pgl@ece.au.dk (main supervisor)
• Associate Professor Claudio Gomes, Claudio.gomes@ece.au.dk (co-supervisor)
  

For information about application requirements and mandatory attachments, please see our application guide. If answers cannot be found there, please contact:

• admission.gradschool.tech@au.dk
  

How to apply:
Please follow this link to submit your application.

Application deadline is 30 January at 23:59 CET.

Preferred starting date is 1 May 2026.

Please note:

• Only documents received prior to the application deadline will be evaluated. Thus, documents sent after deadline will not be taken into account.
• The programme committee may request further information or invite the applicant to attend an interview.
• Shortlisting will be used, which means that the evaluation committee only will evaluate the most relevant applications.
  

Aarhus University’s ambition is to be an attractive and inspiring workplace for all and to foster a culture in which each individual has opportunities to thrive, achieve and develop. We view equality and diversity as assets, and we welcome all applicants. All interested candidates are encouraged to apply, regardless of their personal background. Salary and terms of employment are in accordance with applicable collective agreement.

 

INFORMATIONER OM STILLINGEN:

- Arbejdspladsen ligger i:

Aarhus Kommune

-Virksomheden tilbyder:

-Arbejdsgiver:

Aarhus Universitet, Nordre Ringgade, 8000 Aarhus C

-Ansøgning:

Ansøgningsfrist: 30-01-2026;

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