Assistant Professor in Preventive and Predictive Maintenance

At the Esbjerg Energy Section a position as Assistant Professor in preventive and predictive maintenance with emphasis on condition monitoring and non-destructive testing (NDT) is open for appointments. The duration of the position is 3 years.

The position is full time and is expected to start on 1 July 2026 or as soon as possible thereafter.

Your work tasks
The position is offered in relation to the research groups Multimodal Reasoning for Robotics and Process Intelligence and Underwater Technology and the Assistant Professor will be positioned in the Esbjerg Energy Section.

Research areas will be within preventive and predictive maintenance with a strong focus on condition monitoring and non-destructive testing. The position centres on developing and validating new methods for non-destructive testing and condition monitoring using modern machine learning including multimodal foundation models and related data-driven and physics-informed approaches.

Research topics may include visual and real-time tracking of damage progression forecasting and remaining useful life estimation multisensor fusion robust learning under limited or noisy labels uncertainty-aware decision support and lifecycle and reliability assessment. Within this scope you are expected to drive your own research activities while contributing actively to ongoing projects and collaborative initiatives in the department.

The research will be conducted primarily within the Multimodal Reasoning for Robotics and Process Intelligence and Underwater Technology groups where you will work closely with colleagues and participate in joint activities and project development. A significant part of the research will be carried out in close collaboration with industrial partners particularly within offshore maintenance inspection and operational support. This ensures a strong connection to real-world challenges and a clear pathway for industrial relevance and impact.

Teaching will primarily be in condition monitoring machine learning and dynamical systems or control-oriented modelling within study directions such as Applied Industrial Electronics Energy AI and Autonomous Systems Offshore Energy Systems and related engineering programmes but also in other study groups at Aalborg University. Teaching follows Aalborg Universitys Problem Based Learning model and you will supervise and co-supervise student projects contribute to course development and examinations and take part in the everyday academic life of the department.

Your competencies
The applicant must have a relevant professional and educational background within machine learning deep neural networks computer science dynamical systems or a closely related engineering field. You can document the ability to conduct high-quality research through publications in relevant peer-reviewed venues and you are motivated to further develop your research profile within preventive and predictive maintenance condition monitoring and non-destructive testing.

You have solid experience with modern machine learning methods particularly attention-based neural networks within computer vision and/or natural language processing and you are comfortable working with data-driven approaches to damage detection condition monitoring and forecasting. You are proficient in Linux and Python preferably with experience in PyTorch or a similar deep learning framework and you are able to design and implement robust experimental pipelines.

Experience with sensors embedded systems cameras and optics or thermal imaging will be considered an advantage.

As a colleague you work independently and show initiative in shaping and driving research activities forward while at the same time valuing collaboration in interdisciplinary teams. You contribute positively to a constructive and inclusive working environment communicate your work clearly in both written and spoken form and enjoy supervising and supporting students in their academic and professional development.

Proficiency in English at an academic level is required.

Who we are
You will join a department that combines strong research traditions in energy engineering robotics and applied artificial intelligence with a close connection to industry and society. The research will primarily be anchored in the Underwater Technology and Multimodal Reasoning for Robotics and Process Intelligence research groups which work on advanced robotics perception and intelligent systems for challenging environments such as offshore and underwater domains.
The department offers an international and collaborative research environment with access to modern laboratory facilities experimental platforms and strong industrial networks. Research and education are based on Aalborg Universitys Problem Based Learning model where students work in project groups on real world problems in close dialogue with researchers and external partners. As an assistant professor you will become part of this environment and contribute to further strengthening the link between research teaching and application.

We value an open and inclusive working culture where colleagues support each other and share knowledge across groups and disciplines. You will be part of a team with a mix of senior and junior researchers PhD students and technical staff and you will have good opportunities to develop your academic career research profile and teaching portfolio.

More information about the research groups can be found here:

• requirements
  Appointment as assistant professor requires academic qualifications at PhD level. The research potential of each applicant will be emphasized in the overall assessment.
  
  How to apply
  Your application must include the following:
  • Application stating reasons for applying qualifications in relation to the position and intentions and visions for the position
  • Curriculum Vitae (CV)
  • Diplomas (masters degree diploma and PhD diploma)
  • List of publications with an indication of the attached publications that you wish to be taken into account in the assessment. Youmay attach a maximum of five publications.
  • Documentation of teaching qualifications. Please see guidelines for teaching portfolio at The Technical Faculty of IT and Design The Faculty of Engineering and Science and The Faculty of Medicine.
  • Dissemination qualifications including participation on committees or boards participation in organisations etc.
  • Additional qualifications in relation to the position
  • References/recommendations

  You can read more about the requirements for your application here.

  The application must be submitted via Aalborg Universitys recruitment system which can be accessed under the job advertisement on Aalborg Universitys website.

  Aalborg University wants to reflect the surrounding society and has diversity as a core value. Therefore everyone regardless of personal background and orientation is encouraged to apply for the position.

  Do you have any questions
  If you have any questions about the position you are more than welcome to contact us. You will find contact persons at the bottom of the jobpost.
  
  Further information
  Read more about our recruitment process here

  The appointment process at Aalborg University involves a shortlisting process. You can read more about the shortlisting and appointment process here.

  The hiring process at Aalborg University may include a risk assessment as a tool to identify potential risks associated with new hires ensuring the safety compliance and integrity of the workplace.

  Salary and terms of employment
  The employment is in accordance with the Ministerial Order on the Appointment of Academic Staff at Universities (the Appointment Order) and the Ministerial Order on Job Structure for Academic Staff at Universities (in Danish) and protocol on certain terms of employment of academic staff at universities (in Danish).

  Salary and terms of employment are in accordance with the collective agreement between the Danish Confederation of Professional Associations and the state (AC collective agreement) (only in Danish) and protocol on certain terms of employment of academic staff at universities (only in Danish).
  
  There is a mutual probationary period of 3 months for the position.

Aalborg University - Knowledge for the world
Aalborg University is an international workplace with more than 3700 employees. We offer real-world-oriented education and create world-class research results through collaboration between researchers students and public and private companies. This is how we achieve insights new solutions to societal problems and knowledge that changes the world. Our main campus is in Aalborg but we also have campuses in Esbjerg and Copenhagen.