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.
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, email@example.com.
Read more about AAU at https:// www. aau.dk .
Read more about the AAU Energy at www. energy.aau.dk.
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
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.
The applications are only to be submitted online by using the "Apply online"
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
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 firstname.lastname@example.org
Information regarding guidelines, ministerial circular in force and procedures
can be seen here
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