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Faculty of Information Technology and Electrical Engineering

Department of Electronic Systems (IES)

PhD Research Fellowship position to "STARS: Statistical learning for autonomous resource constrained sensors" at the Department of Electronic Systems

The Faculty of Information Technology and Electrical Engineering, at the Norwegian University of Science and Technology (NTNU) has a vacancy for a 100% position as a PhD Research fellow at the Department of Electronic Systems (IES) (http://www.ntnu.edu/ies). This fellowship is one out of two positions granted by NTNU in support of "enabling technologies within ICT."The PhD project involves a cross-disciplinary supervisory team from Department of Electronic Systems (IES), Department of Information Security and Communication Technology (IIK), and Department of Mathematical Sciences (IMF).

The PhD position is for up to 4 years with 25% work assignments for NTNU.

Information about the department

Currently IES has approximately 165 full-time employees spread across 45 professors/ass professors, 70 PhD, 25 research/Post.Doc and 25 engineering/administration.

IES has the principal responsibility for education and research in electronics at NTNU. IES research portfolio comprises the areas of wireless communication, marine acoustics/sub-sea communications, multimedia and speech technology, micro- and nano-technology, sensors, and medical technology.

Project description

Smart cities require an intelligent infrastructure that is autonomous, dependable, and resilient to natural or man-made disturbances. Such infrastructure connects myriads of "things" (sensors, actuators, machines, etc.) through the internet, forming the Internet of Things (IoT). Thanks to the continuous improvement of technologies, today’s sensors are more capable than simply collecting data and can perform some, albeit simple, operations that make them more autonomous. Nevertheless, IoT sensors are extremely constrained devices and it is critical to ensure frugal usage of energy by minimizing computation, storage and data transmission. Sensors find themselves in heterogeneous and non-stationary environments and, due to the sheer scale of IoT, it is impossible for engineers to manually optimize each sensor. Thus, providing the same (static) configuration and behavior to each sensor results in inefficient solutions, which leads to battery depletion or over-dimensioned, expensive systems. As of today, the collected data are not fully exploited to improve the operation and maintenance of the supporting measurement infrastructure itself. This is the starting point of this ambitious project.

This project will focus on the development and analysis of cloud-based machine learning approaches to enable energy-efficient and autonomous sensor systems at large scales. The goal is to increase situation-awareness of sensors by providing them with intelligence to locally adjust their measurement and reporting rates according to the situation at hand and the overall status of the data acquisition. For this purpose, bidirectional communication will be exploited to allow machine learning algorithms in the cloud to interact with IoT sensor nodes to enable more selective sensing, processing and communication. Developed ideas can be tested and implemented in practice on the existing IoT platform at NTNU that is part of the NTNU Internet of Things Lab at IIK.


We seek a highly-motivated individual holding a master’s degree in signal processing, statistical machine learning, applied mathematics, optimization (specifically in wireless sensor networks) or other relevant disciplines. A strong mathematical background and a research-oriented master thesis within one of these areas is expected. Further, the applicants must have experience with programming. Publication activities in the aforementioned disciplines will be considered an advantage. Motivation for fundamental scientific research of practical relevance is essential. The candidate is expected to deliver several journal articles within the duration of the project. The applicant should have good communication skills and be willing to collaborate with other researchers in the cross-disciplinary group of people connected to this project. Applicants are asked to provide a research statement (max 3 pages) in their application, describing research interests and initial plans with regards to the above project description. The statement should also provide details on how the project relates to previous education, research and competence.

Applicants who do not master a Scandinavian language must provide evidence of good written and spoken English language skills. The following tests can be used as documentation: TOEFL, IELTS, 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.

The application

The application must contain information of educational background and prior training, exams, and work experience. In addition, we ask the applicant to submit a research statement (max 3 pages), detailing research interests and initial plans with regard to the project description above. The statement should also describe why the applicant is suited for the position, and how the project relates to previous education, research and competence. Publications and other work that the applicant wishes to be taken into account must be enclosed (including a brief description of the contribution if not obvious). Incomplete applications will not be taken into consideration.

Starting date no later than 01.09.2017.


The appointment is made in accordance with the regulations 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 participate in an organized PhD programme of study during their period of employment. The candidate appointed must comply with the regulations for employees in the public sector. In addition, a contract will be signed regarding the period of employment.

Applicants must be qualified for admission to a PhD study program at NTNU. See http://www.ntnu.edu/ie/research/phd for information about PhD studies at NTNU.

We can offer

  • an informal and friendly workplace with dedicated colleagues
  • academic challenges in a cross-disciplinary team
  • attractive schemes for home loans, insurance and pensions through the Norwegian Public Service Pension Fund

For further information about the position, contact Professor Stefan Werner, email: stefan.werner@ntnu.no . 

Depending on qualifications and academic background, PhD Candidates (in code 1017) at the Faculty of Information Technology and Electrical Engineering will be remunerated at a minimum of NOK 435 100 per year before tax. Normal wage level is NOK 435 100 - 488 900 of which 2% is deducted for the Norwegian Public Service Pension Fund.

The appointment is subject to the conditions in effect at any time for employees in the public sector.

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.

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.

Applicants are kindly 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.

The application with a CV and certified copies of diplomas and certificates must be sent electronically via this page with information about education and relevant experience (all in one combined PDF file).

Mark the application IE 040-2017.

Deadline for applications: 2017-04-18.



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Om stillingen

  • Søknadsfrist
    18. april 2017
  • Arbeidsgiver
    NTNU - Norges teknisk-naturvitenskapelige universitet
  • Nettside
  • Kommune
  • Arbeidssted
  • Jobbnorge-ID
  • Intern-ID
    IE 040-2017
  • Omfang
  • Varighet

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