About the job
For a position as a PhD Candidate, the goal is a completed doctoral education up to an obtained doctoral degree.
Are you seeking an exciting Ph.D. opportunity combining cutting-edge research with real-world impact? Do you have a passion for privacy-preserving machine learning and recommender systems? If so, we have the perfect opportunity for you. We are looking for a talented and motivated Ph.D. student to join our research team in the Privacy@Edge project and work on the problem of recommender systems for privacy settings using federated learning on the network edge. The project is funded by the Research Council of Norway and is in collaboration between SINTEF Digital, a leading research organization in Norway, NTNU, and several industrial partners.
As a Ph.D. student in our team, you will work on developing innovative federated learning techniques on the network edge to address the problem of recommender systems for individual user privacy settings. This is a critical area of research as users increasingly demand personalized recommendations while demanding their privacy to be respected. You will be able to work on cutting-edge machine learning and privacy research and collaborate with leading researchers in the field. You will be part of a dynamic and collaborative team committed to pushing the boundaries of research and making a real-world impact. Join us and make a difference in the future of privacy-preserving machine learning.
The Ph.D. candidates will have the opportunity to be affiliated with the IoT@NTNU and with the Norwegian Open AI lab, and to collaborate with research scientists from international partner institutions.
Your immediate leader is the Head of the Department.
Duties of the position
- Submitting an application for admission and a research plan no later than three (3) months after the employment.
- Undertaking the necessary courses (30 ECTS) as part of the PhD program.
- Conducting high-quality research and reporting progress regularly and in agreement with the supervisors.
Required selection criteria
- You must have a professionally relevant background in Electrical Engineering, Computer Science, Applied Mathematics, or other relevant disciplines.
- Your education must correspond to a five-year Norwegian degree program, where 120 credits are obtained at the master’s level.
- You must have a strong academic background from your previous studies and an average grade from the master’s degree program or equivalent education, equal to B or better than NTNU’s grading scale. If you do not have letter grades from previous studies, you must have an equally good academic basis. If you have a weaker grade background, you may be assessed if you can document that you are particularly suitable for a PhD education.
- You must have a strong mathematical background and a research-oriented master thesis in a related field (e.g., signal processing, statistical machine learning, applied mathematics).
- You must have significant experience with programming (preferably Matlab and/or Python).
The appointment is to be made in accordance with Regulations on terms of employment for positions such as postdoctoral fellow, Phd candidate, research assistant and specialist candidate and Regulations concerning the degrees of Philosophiae Doctor (PhD) and Philosodophiae Doctor (PhD) in artistic research national guidelines for appointment as PhD, post doctor and research assistant
Preferred selection criteria
- Experience in machine learning on edge, IoT, and recommender systems.
- Publication activity in aforementioned topics.
- Excellent written and oral English skills.
- Scientifically curious and open to new research challenges.
- Independent, persistent, and self-motivated in addressing technical problems.
- Flexible and reliable, with the ability to work efficiently independently and as part of a team.
- Committed with respect to deadlines.
- Excellent with verbal and written communication in English.
Emphasis will be placed on personal and interpersonal qualities.
- exciting and stimulating tasks in a strong international academic environment
- an open and inclusive work environment with dedicated colleagues
- favourable terms in the Norwegian Public Service Pension Fund
- employee benefits
Salary and conditions
As a PhD candidate (code 1017) you are normally paid from gross NOK 532 200 per annum before tax, depending on qualifications and seniority. From the salary, 2% is deducted as a contribution to the Norwegian Public Service Pension Fund.
The period of employment is four (4) years (with 25 % teaching duties).
Appointment to a Ph.D. position requires that you are admitted to the Ph.D. programme in Electronics and Telecommunications within three months of employment and that you participate in an organized PhD programme during the employment period.
The engagement is to be made in accordance with the regulations in force concerning State Employees and Civil Servants, and the acts relating to Control of the Export of Strategic Goods, Services and Technology. Candidates who by assessment of the application and attachment are seen to conflict with the criteria in the latter law will be prohibited from recruitment to NTNU.
After the appointment you must assume that there may be changes in the area of work.
It is a prerequisite you can be present at and accessible to the institution daily.
About the application
The application and supporting documentation to be used as the basis for the assessment must be in English.
Publications and other scientific work must follow the application. Please note that your application will be considered based solely on information submitted by the application deadline. You must therefore ensure that your application clearly demonstrates how your skills and experience fulfil the criteria specified above.
The application must include:
- Cover letter describing your motivation (1 page).
- CV (including information about educational background and working experience) and certificates.
- Transcripts and diplomas for bachelor’s and master’s degrees.
- Brief research vision for the position (maximum 2 pages).
- Name and contact information of three referees.
- List of publications or other relevant research work (if any).
- Documentation of fluency in the English language (if any).
- If already submitted, a copy of the master’s thesis (documentation of a completed master’s degree must be presented before taking up the position).
If all, or parts, of your education has been taken abroad, we also ask you to attach documentation of the scope and quality of your entire education, both bachelor’s and master’s education, in addition to other higher education. Description of the documentation required can be found here. If you already have a statement from NOKUT, please attach this as well.
We will take joint work into account. If it is difficult to identify your efforts in the joint work, you must enclose a short description of your participation.
In the evaluation of which candidate is best qualified, emphasis will be placed on education, experience and personal and interpersonal qualities. Motivation, ambitions, and potential will also count in the assessment of the candidates.
NTNU is committed to following evaluation criteria for research quality according to The San Francisco Declaration on Research Assessment – DORA.
NTNU believes that inclusion and diversity is our strength. We want to recruit people with different competencies, educational backgrounds, life experiences and perspectives to contribute to solving our social responsibilities within education and research. We will facilitate for our employees’ needs.
NTNU is working actively to increase the number of women employed in scientific positions and has a number of resources to promote equality.
The city of Trondheim is a modern European city with a rich cultural scene. Trondheim is the innovation capital of Norway with a population of 200,000. The Norwegian welfare state, including healthcare, schools, kindergartens and overall equality, is probably the best of its kind in the world. Professional subsidized day-care for children is easily available. Furthermore, Trondheim offers great opportunities for education (including international schools) and possibilities to enjoy nature, culture and family life and has low crime rates and clean air quality.
As an employee at NTNU, you must at all times adhere to the changes that the development in the subject entails and the organizational changes that are adopted.
A public list of applicants with name, age, job title and municipality of residence is prepared after the application deadline. If you want to reserve yourself from entry on the public applicant list, this must be justified. Assessment will be made in accordance with current legislation. You will be notified if the reservation is not accepted.
If you have any questions about the position, please contact Professor Stefan Werner, email email@example.com. If you have any questions about the recruitment process, please contact Lars Arne Hassel, e-mail: firstname.lastname@example.org.
If you think this looks interesting and in line with your qualifications, please submit your application electronically via jobbnorge.no with your CV, diplomas and certificates attached. Applications submitted elsewhere will not be considered. Upon request, you must be able to obtain certified copies of your documentation.
Application deadline: 05.06.23
NTNU – knowledge for a better world
NTNU – knowledge for a better world
The Norwegian University of Science and Technology (NTNU) creates knowledge for a better world and solutions that can change everyday life.
Department of Electronic Systems
The digitalization of Norway is impossible without electronic systems. We are Norway’s leading academic environment in this field, and contribute with our expertise in areas ranging from nanoelectronics, phototonics, signal processing, radio technology and acoustics to satellite technology and autonomous systems. Knowledge of electronic systems is also vital for addressing important challenges in transport, energy, the environment, and health. The Department of Electronic Systems is one of seven departments in the Faculty of Information Technology and Electrical Engineering .