PhD Scholarship in Machine Learning-based Detection and Categorization for Robust Autonomous Ship Perception

fredag 19 jul 19

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Frist 15. september 2019
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The Automation and Control Group at the Department of Electrical Engineering invites applicants for 3-years PhD position in the area of Machine Learning-based Detection and Categorization for Robust Autonomous Ship Perception. The goal of this PhD project is to develop novel and robust vision algorithms for object detection and categorization, to be used on ships during autonomous operation.

The PhD project is funded by the ShippingLab Autonomy Work Package (WP). Thus, this PhD project will be an integral part of a broader research team, consisting of multiple PhD students and senior academic staff. The research team will focus on vision-based machine learning for object detection in sea, as well as on multi-sensor state estimation for ship perception.

The PhD candidate will participate in measurements, test and validation at sea. The candidate is expected to be dedicated, productive and ambitious team player, who wish to obtain an international level in her/his area. Scientific publication and experimental validation of results will be part of the PhD project. Presentation at international conferences will be part of the research training and elements of didactics will be obtained through experience as a teaching assistant. The PhD student will have the opportunity to work together with high profile partners in the maritime domain, since the Autonomy WP of the ShippingLab project is a joint effort between DTU (Kgs. Lyngby), SIMAC, Wärtsila-Lyngsø Marine, Logimatic Engineering, Danelec Marine, TUCO Marine, DFDS, Danske Færger and a Harbor Bus Operator.

Responsibilities and tasks
Are you interested in autonomous ships? The goal of this PhD project is to develop novel and robust algorithms for object detection and categorization, to be used on ships during autonomous operation.

You will be responsible for research of methods and deep learning architectures in combination with other techniques. Your goal will be the analysis of images, and possibly of data from further sensors, such that detection and categorization errors are minimized. Your research will include incremental updating of recognition models as experience is accumulated. The developed techniques need to enable operability over long periods of time, supporting safe operation at all times.

Your research will revolve around:
 

  • Incremental learning,
  • Deep learning,
  • Robust, long-term estimation.

Qualifications
Candidates should have a two-year master's degree (120 ECTS points) in Robotics, Electrical Engineering, Computer Science or equivalent, or a similar degree with an academic level equivalent to a two-year master's degree.

Additionally:
  • Specialization in machine learning or robot vision would be an advantage.
  • Experience with open-source tools for machine learning and robot vision would be an advantage.
  • Familiarity with design of convolutional neural networks architectures would be an advantage.
Approval and Enrolment
The scholarship for the PhD degree is subject to academic approval, and the candidate will be enrolled in one of the general degree programmes at DTU. For information about our enrolment requirements and the general planning of the PhD study programme, please see the DTU PhD Guide.   

Assessment
The research of this project has civilian objectives. However, equipment restricted by export licenses and ITAR (International Traffic in Arms Regulations) is being used in this research. Applicants that are citizens of Denmark, Norway and other NATO countries, Sweden, Australia, New Zealand, or Japan are eligible. Other applicants should provide evidence of eligibility to use such equipment for their application to be considered.

We offer
DTU is a leading technical university globally recognized for the excellence of its research, education, innovation and scientific advice. We offer a rewarding and challenging job in an international environment. We strive for academic excellence in an environment characterized by collegial respect and academic freedom tempered by responsibility.

Salary and appointment terms
The appointment will be based on the collective agreement with the Danish Confederation of Professional Associations. The allowance will be agreed upon with the relevant union. The period of employment is 3 years. 

You can read more about 
career paths at DTU here.   

Further information
Further information may be obtained by contacting Associate Professor Lazaros Nalpantidis, lanalpa@elektro.dtu.dk or +45 5162 1776.  

You can read more about Automation and Control Group at the Department of Electrical Engineering 
www.aut.elektro.dtu.dk

Application
Please submit your online application no later than 15 September 2019 (local time)Applications must be submitted as one PDF file containing all materials to be given consideration. To apply, please open the link "Apply online", fill out the online application form, and attach all your materials in English in one PDF file. The file must include: 
  • A letter motivating the application (cover letter)
  • Curriculum vitae
  • Grade transcripts and BSc/MSc diploma
  • Excel sheet with translation of grades to the Danish grading system (see guidelines and Excel spreadsheet here)

Candidates may apply prior to obtaining their master's degree but cannot begin before having received it.

Applications and enclosures received after the deadline will not be considered.

All interested candidates irrespective of age, gender, race, disability, religion or ethnic background are encouraged to apply.

DTU Electrical Engineering educates students within electrical engineering technologies. We offer studies at BEng, BSc, MSc and PhD levels, and participate in joint international programmes. We conduct state-of-the-art research within antenna and microwave technology, robot technology, power and physical electronics, acoustic environment, electro-acoustics, electric power and energy. Our department has more than 200 members of staff.

DTU is a technical university providing internationally leading research, education, innovation and scientific advice. Our staff of 6,000 advance science and technology to create innovative solutions that meet the demands of society, and our 11,200 students are being educated to address the technological challenges of the future. DTU is an independent university collaborating globally with business, industry, government and public agencies.