Research assistant in IoT data, AI and digital twin technology

Department of Electrical and Computer Engineering; Favrskov Kommune; On-site; DKK 400,000 - 440,000; Full time

Benefits offered by this job

Research infrastructure

International environment

Co-authored publications

PhD pathway

Job summary

Aarhus University invites applications for a 6-month Research Assistant position in the Robots4Green project, working on IoT data, AI and digital twin technology. The position is based in Aarhus, Denmark, starting 1 January 2027 or as soon as possible.

You will develop models for IoT data and digital twins, train ML models for forecasting and anomaly detection, and contribute to data pipelines and model integration.

Qualifications

• Master's degree in a relevant field (EE, CS, Data Science)
• Strong Python programming and ML framework experience
• Solid foundation in statistics and signal processing
• Good time-series analysis capabilities

Responsibilities

• Apply signal processing and feature extraction to sensor time series
• Design, train and evaluate ML models for forecasting and anomaly detection
• Contribute to data pipelines and integration with a digital twin platform
• Support experiments and demonstrations with project partners
• Document results and contribute to publications and deliverables

Skills

Python programming

Machine learning

Statistics

Time series analysis

Education

Master's degree in Electrical Engineering

Master's degree in Computer Engineering

Master's degree in Computer Science

Master's degree in Data Science

Tools

scikit-learn

PyTorch

Job description

Research assistant in IoT data, AI and digital twin technologyAre you interested in turning IoT data into intelligent digital twins of real-world systems? The Department of Electrical and Computer Engineering at Aarhus University invites applications for a 6-month research assistant position in the Robots4Green project, working at the intersection of IoT data, artificial intelligence and digital twin technology. The position is based in Aarhus, Denmark, and starts on 1 January or as soon as possible thereafter.

Expected start date and duration of employmentThis is a 6-month position from 1 January 2027 or as soon as possible thereafter.

Job descriptionWe are seeking a motivated research assistant with a strong background in data science and machine learning to contribute to research on AI for IoT data and digital twin technology. You will work with sensor data and develop the models that allow digital twins to monitor, understand and predict the behaviour of physical systems.

Your tasks will include:

• Applying signal processing and feature extraction methods to sensor time series, for example wind and environmental data
• Designing, training and evaluating machine learning models for forecasting and anomaly detection, with an emphasis on interpretable and reliable models
• Contributing to data pipelines and to the integration of models into a digital twin platform together with the project team
• Supporting experiments and demonstrations together with project partners
• Documenting results and contributing to scientific publications and project deliverables

The position may also include assisting in supervision activities at the department.

Prior experience with IoT or digital twins is an advantage. You will gain hands on experience with IoT data and digital twin technology while working closely with researchers in the Networks and Analytics research group and with academic and industrial partners in the project. The position is an excellent stepping stone towards a PhD or a career in industry.

Your profileApplicants should hold a Master's degree in Electrical Engineering, Computer Engineering, Computer Science, Data Science or a similar field.

We are looking for candidates with:

• Solid programming skills in Python for data analysis and modelling
• Experience with machine learning frameworks such as scikit-learn and PyTorch or similar AI frameworks
• A strong foundation in statistics, probability and signal processing
• A good understanding of time series analysis

The following qualifications are considered advantages:

• Experience with graph-based machine learning, such as graph neural networks, or graph signal processing
• Knowledge of IoT systems, sensor data or data platforms
• Familiarity with digital twin concepts and simulation
• Experience from research projects, including interdisciplinary collaborations
• Teaching or supervision experience

Personal skillsWe value good communication skills in English, the ability to work independently as well as in an international team, curiosity and a proactive, structured approach to problem solving.

Who we areThe Department of Electrical and Computer Engineering (ECE) at Aarhus University is a leading research institution with strong expertise in computer science, electrical engineering and wireless communication systems. We maintain active collaborations with industry partners and are involved in multiple national and international research projects on IoT, AI and digital twins.

You will be joining the Networks and Analytics (NAN) research group, which focuses on research and innovation in developing and applying internet technology across a wide selection of fields in electrical and computer engineering for real-world, large-scale applications. The NAN group has strong expertise in wireless networks, IoT, network security, data analytics, AI and cooperative multi agent systems, with extensive experience in smart energy grids, smart and integrated transport and satellite communication systems.

Our research group provides a dynamic and supportive environment where interdisciplinary collaboration is encouraged, and where you will work with both academic researchers and industry professionals on projects with real world impact.

Department website: https://ece.au.dk

What we offerThe Department of Electrical and Computer Engineering offers:

• An exciting opportunity to work on applied research in IoT data, AI and digital twin technology
• A well developed research infrastructure with access to laboratories, IoT equipment and computing facilities
• Close collaboration with industrial partners and direct pathways to real world validation
• An interdisciplinary and international research environment
• Opportunities to co-author scientific publications and build a foundation for a PhD
• A supportive work environment that values work-life balance, professional development and openness

Place of work and area of employmentThe place of work is Helsingforsgade 10, 8200 Aarhus N (Denmark), and the area of employment is Aarhus University with related departments.

Contact informationFor further information, please contact: Professor Rune Hylsberg Jacobsen, ,

DeadlineApplications must be received no later than 17 November 2026.

Formalities and salary rangeNatural Sciences refers to the Ministerial Order on the Appointment of Academic Staff at Danish Universities under the Danish Ministry of Science, Technology and Innovation.

The application must be in English and include a curriculum vitae, degree certificate, a complete list of publications, a statement of future research plans and information about research activities, teaching portfolio and verified information on previous teaching experience (if any). Guidelines for applicants can be found here.

Appointment shall be in accordance with the collective labour agreement between the Danish Ministry of Taxation and the Danish Confederation of Professional Associations. Further information on qualification requirements and job content may be found in the Memorandum on Job Structure for Academic Staff at Danish Universities.

Salary and terms as agreed between the Danish Ministry of Taxation and the Confederation of Professional Unions at basic salary steps 4-8.

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.