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Postdoc in Deep Learning Methods for Condition Monitoring (2022-224-03919)

At the Faculty of Engineering and Science, AAU Energy, a position as Postdoc in Deep Learning Methods for Condition Monitoring is open for appointment from 1st May 2022 – 30st April 2025 or soon hereafter.

Job description

Aalborg University contributes to the knowledge building of the global society as well as the development of prosperity, welfare and culture of Danish society. This is accomplished through research, research-based education, public sector services and knowledge collaboration. Aalborg University educates students for the future and activities are based on a dynamic and transformative collaboration with the surrounding community. 

AAU Energy is a dynamic engineering research department in continuous growth and inspiring surroundings. AAU Energy has a very international environment and covers all areas of clean and sustainable energy systems of the future within electrical, thermal and mechatronic energy technology. AAU Energy has campuses in both Aalborg and Esbjerg, this position is in Esbjerg. 

The mission is to be world leading in both research and research-based education of the energy engineers of the future. AAU Energy has approx. 300 employees of many nationalities, of which 25 are administrative staff. In addition, AAU Energy constantly has approximately 50-70 guest researchers from around the world. 

Research and teaching are in the absolute world elite in the field of energy, and we have extensive and leading workshop and laboratory facilities, where research and innovation are carried out in direct collaboration with industry to a great extent. 

The position is offered in relation to the research program (OFFSHORE DRONES AND ROBOTICS) and the Postdoc will be positioned to the section in Esbjerg.

The post-doctoral fellowship is part of the project - Building the foundation for the use of fiber rope in cranes for tall wind turbines, funded by EUDP (Energy Technology Development and Demonstration Program). The project investigates the possibility of replacing steel wire ropes for self-hoisting cranes with Ultra-high-molecular-weight-polyethylene (UHMWPE/Dyneema) fiber ropes.  One of the key tasks in this study is to develop a method for condition monitoring of fiber ropes. The goal is to enable automatic on-line tracking of rope degradation that can be used for preventive and predictive maintenance. This involves a visual real-time tracking of minor damage developments through the life cycle of the rope.

The post-doctoral candidate must have demonstrated the ability to carry out high quality research within the topic of the offered position, by publishing articles in recognized peer-reviewed journals relevant to the field. Qualified applicants ideally must have a PhD degree in a topic related to machine learning, deep neural networks, computer science or similar engineering fields. A highly independent and proactive attitude will be appreciated.

Expected qualifications of the candidate include the knowledge of attention-based networks or convolutional neural networks with application in computer vision along with experience in damage detection, condition monitoring and forecasting methods. The applicant is expected to be familiar with: Linux, Python (Pytorch, TensorFlow). Knowledge within Embedded systems, camera and optics, and communication protocols is advantageous. Proficiency in English, both spoken and written is required.  

You may obtain further professional information from Associate Professor Petar Durdevic, +45 31751320, pdl@energy.aau.dk.

Read more about AAU at http://www.aau.dk .

Read more about the AAU Energy at www.energy.aau.dk. 

 

Qualification requirements: 

Appointment as Postdoc presupposes scientific qualifications at PhD–level or similar scientific qualifications. The research potential of each applicant will be emphasized in the overall assessment. Appointment as a Postdoc cannot exceed a period of four years in total at Aalborg University.

The application must contain the following:

  • A motivated text wherein the reasons for applying, qualifications in relation to the position, and intentions and visions for the position are stated.
  • A current curriculum vitae.
  • Copies of relevant diplomas (Master of Science and PhD). On request you could be asked for an official English translation.
  • Scientific qualifications. A complete list of publications must be attached with an indication of the works the applicant wishes to be considered. You may attach up to 5 publications.
  • Dissemination qualifications, including participation on committees or boards, participation in organisations and the like.
  • Additional qualifications in relation to the position. References/recommendations.
  • Personal data.

The applications are only to be submitted online by using the "Apply online" button below.

Shortlisting will be applied. After the review of any objections regarding the assessment committee, the head of department, with assistance from the chair of the assessment committee, selects the candidates to be assessed. All applicants will be informed as to whether they will advance to assessment or not.

AAU wishes to reflect the diversity of society and welcomes applications from all qualified candidates regardless of personal background or belief.

For further information concerning the application procedure, please contact Mathilde Vestergaard HR-Servicecentre EST by mail est-ef-hr@adm.aau.dk

Information regarding guidelines, ministerial circular in force and procedures can be seen here 

Agreement

Employment is in accordance with the Ministerial Order on the Appointment of Academic Staff at Universities (the Appointment Order) and the Ministry of Finance's current Job Structure for Academic Staff at Universities. Employment and salary are in accordance with the collective agreement for state-employed academics.   

Vacancy number

2022-224-03919

Deadline

08/02/2022

Apply online
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