NORWEGIAN UNIVERSITY OF SCIENCE & TECHNOLOGY -NTNU

PhD Position in Sensor Fusion for Digital Transformation Project

3 days left

Location
Trondheim, Norway
Posted
19 Apr 2018
End of advertisement period
27 May 2018
Ref
IE-080-2018
Contract Type
Temporary
Hours
Full Time

The Norwegian University of Science and Technology (NTNU) is now launching a strategic research program called Digital transformation with nine research projects. One of these projects is about the development of autonomous all-electric passenger ferries for urban water transport (Autoferry). Succeeding with the Autoferry project requires a broad multi-disciplinary approach and involves six PhD positions. The position announced here is on the topic of Sensor fusion, and is affiliated with the Department of Engineering Cybernetics (ITK) at the Faculty of Information Technology and Electrical Engineering. The place of work is in Trondheim.

Information about the department

ITK has 25 professors, 17 adjunct professors, about 15 postdocs and researchers as well as 70 PhD candidates. The research and educational activities at ITK include both fundamental and applied activities in areas such as automatic control and systems theory, estimation and optimization, cyber-physical systems, autonomous unmanned vehicles, robotics, process control, smart grids, biomedical technology, embedded and real-time systems, and aquaculture cybernetics. The department is involved in numerous research projects and centers, including the Centre of Excellence for Autonomous Marine Operations and Systems (NTNU AMOS).

Work description

This is a researcher training position aimed at providing promising researcher recruits the opportunity of academic development in the form of a doctoral degree.

Autonomous surface vehicles (ASVs) need sophisticated systems for guidance, motion control, docking and perception of its surroundings. Possible sensors such as FMCW radar, automotive lidar, optical cameras and infrared cameras all have their strengths and weaknesses. The ASV must therefore combine inputs from the different sensors through sensor fusion in order to obtain an adequate world image and situational awareness. The sensor data are interpreted through methods for multi-target tracking and simultaneous localization and mapping (SLAM) in order to perform tasks such as navigation, collision avoidance and docking. These methods must work in real time and exhibit sufficient robustness to noisy, missing or faulty data.

The topic of this PhD project is sensor fusion for autonomous surface vehicles, with a particular focus on autonomous urban ferries. The goal of this project is to achieve a multi-sensor fusion system which provides reliable situational awareness, consisting of both on-shore and on-board sensors. Sensors placed at strategic locations both on-shore and on-board will enable the ferry to sense as much as possible. Specifically, this PhD position will consider architectures for shore-to-vessel sensor fusion using radar, lidar and a 360-degree thermal camera; active-passive sensor fusion using methods for target tracking to fuse data from active sensors (radar and lidar) with passive sensors (thermal camera) in real time; and implementation of shore-to-vessel sensor fusion for docking, which entails fusion of the inertial navigation system with data from the lidar and radar transponders.

The research will be carried out in an interdisciplinary environment under guidance of four supervisors from the Department of Engineering Cybernetics (ITK), the Department of Electronic Systems (IES) and the Department of Computer Science (IDI). At ITK, the PhD fellow will collaborate closely with two other PhD candidates working on sensor fusion and collision avoidance for the autonomous ferry. The PhD candidate is expected to make research contributions in fields such as multi-target tracking, SLAM and machine learning, while also taking a main responsibility in experimental validation of the systems.

Qualifications

We seek an ambitious and highly-motivated individual with a master’s degree in cybernetics, applied mathematics (including statistics), signal processing, marine technology and/or computer science. Experience with machine vision and/or other relevant sensors is expected. The candidate should have a research oriented master’s thesis covering radar, computer vision, machine learning, SLAM, target tracking and/or sensor fusion. Working knowledge of Linux, ROS and C++ will be an important advantage. Motivation for fundamental scientific research of practical relevance is essential.

Academic results, publications, relevant specialization, work or research experience, personal qualifications and motivation will be considered when evaluating the applicants.

The appointment is for a term of 3 years without teaching assistance, or up to 4 years including 25% of teaching assistance.

See here for regulations concerning appointment and promotion to teaching and research posts: https://www.regjeringen.no/no/dokumenter/regulations-concerning-appointment-and-promotion-to-teaching-and-research-posts/id2519258/.

Language requirements

Applicants who do not master a Scandinavian language must provide evidence of good English language skills, written and spoken. The following tests can be used as such documentation: TOEFL, IELTS or Cambridge Certificate in Advanced English (CAE) or Cambridge Certificate of Proficiency in English (CPE). Minimum scores are:

  • TOEFL: 600 (paper-based test), 92 (Internet-based test)
  • IELTS: 6.5, with no section lower than 5.5 (only Academic IELTS test accepted)
  • CAE/CPE: grade B or A.

Formal regulations

Appointments are made in accordance with the regulations in force regarding terms of employment for PhD candidates issued by the Ministry of Education and Research, with relevant parts of the additional guidelines for appointment as a PhD candidate at NTNU.

Applicants must undertake to participate in an organized PhD programme of study during their period of employment. The person who is appointed must comply with the conditions that apply at any time to employees in the public sector. In addition, a contract will be signed regarding the period of employment.

Candidates completing their MSc-degree in the Spring 2018 are encouraged to apply. The position is also open for integrated PhD for NTNU students starting their final year of their master degree in Autumn 2018, see https://www.ntnu.no/ie/forskning/integrertphd for information about integrated PhD.

It is a prerequisite that the successful applicant applies for and is granted admission to the relevant PhD study program as soon as possible after employment. NTNU’s PhD regulations require a master’s degree or equivalent with at least 5 years of studies, and an average ECTS grade of A or B within a scale of A-E for passing grades (A best). Applicants must be qualified for admission as PhD students at NTNU. See https://www.ntnu.edu/ie/research/phd for more information.

See here for regulations concerning appointment and promotion to teaching and research posts: https://www.regjeringen.no/no/dokumenter/regulations-concerning-appointment-and-promotion-to-teaching-and-research-posts/id2519258/

Salary conditions

The position is in code 1017 Research fellow, and is remunerated at a gross NOK 436.900 – 537.700 per year, depending on qualifications. A deduction of 2% is made as a statutory contribution to the Norwegian Public Service Pension Fund.

General

NTNU can offer an informal and friendly workplace with dedicated colleagues, academic challenges and attractive schemes for home loans, insurance and pensions in the Norwegian Public Service Pension Fund.

The Faculty of Information Technology and Electrical Engineering wants to attract outstanding and creative candidates who can contribute to our ongoing research activities. We believe that diversity is important to achieve a good, inclusive working environment. We encourage all qualified candidates to apply, regardless of the gender, disability or cultural background.

The appointment is subject to the conditions in effect at any time for employees in the public sector, and assessments regarding the legislations regulating export control and knowledge transfer.

Under Section 25 of the Freedom of Information Act, information about the applicant may be made public even if the applicant has requested not to have his or her name entered on the list of applicants.

Further details about the position can be obtained from Associate Professor Edmund Førland Brekke (edmund.brekke@ntnu.no).

Application requirements

Applications are to be submitted electronically through this page (www.jobbnorge.no). Preferably, all attachments should be combined into a single file.

The application must contain:

  • CV including information relevant for the qualifications and contact information for at least 2 reference persons
  • Certified copies of academic diplomas and transcripts
  • Applicants from universities outside of Norway are requested to send a diploma supplement (or a similar document) which describes in detail the study and grading system, and the rights for further studies associated with the obtained degree
  • A short research statement (max. 3 pages) including:
    • A short presentation of the motivation for a PhD study
    • Why the applicant is suited for the position
    • The applicant’s view of research challenges for the PhD position

Publications and any other work that the applicant wishes to be considered must also be enclosed. Joint works will be considered if a short summary outlining the applicant's contributions is attached.

Incomplete applications will not be considered.

Mark the application with the reference number: IE-080-2018

Application deadline: May 27, 2018

About this job

  • Deadline Sunday, May 27, 2018
  • Employer NTNU - Norwegian University of Science and Technology
  • Website
  • Municipality Trondheim
  • Place of service Trondheim
  • Jobbnorge ID 151523
  • Internal ID 2018/10946
  • Scope Fulltime
  • Duration Temporary

About applications

  • Applications on this job are registered in an electronic form on jobbnorge.no
  • You must complete: Standard CV
  • Please refer to where you first saw this job advertised!

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