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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 Computer Science
We are the leading academic IT environment in Norway, and offer a wide range of theoretical and applied IT programmes of study at all levels. Our subject areas include hardware, algorithms, visual computing, AI, databases, software engineering, information systems, learning technology, HCI, CSCW, IT operations and applied data processing. The Department has groups in both Trondheim and Gjøvik. The Department of Computer Scienceis one of seven departments in the Faculty of Information Technology and Electrical Engineering.
1 PhD Position in Unsupervised and Interpretable Statistical Learning for Sequential Data
Jobbnorge ID: 174898
This is NTNU
At NTNU, creating knowledge for a better world is the vision that unites our 7 000 employees and 40 000 students.
We are looking for dedicated employees to join us.
About the position
We have a vacancy for one PhD Research Fellow position at the Department of Electronic Systems (IES). The PhD position is for up to 4 years with 25% work assignments for NTNU IES.
The position reports to head of department
Main duties and responsibilities
Sequential data is at the core of most real life application of machine learning and artificial intelligence. Speech recognition and synthesis, human activity recognition and robot navigation are some classical examples, but also monitoring of biometric signals and tracking of devices in mobile telecommunications and internet-of-things involve sequential data.
The machine learning methods used to solve these problems typically rely on large amounts of annotated data. This poses a number of problems:
- the high cost of producing annotations limits the applicability of the methods to domains or user groups that do not justify the cost. For speech technology, for example, this is the case for languages spoken by fewer speakers, or by speaker groups that for geographical, physical or psychical condition diverge from the standard speakers.
- the representations to use and target classes to be learned must be decided in advance by the researches in order to instruct the annotators.
- life-long (open-ended) learning, after the system is deployed, is not possible because it would require human supervision at low signal level.
In addition, the methods that are currently most successful are not easily interpretable, which limits their flexibility and the fundamental knowledge that can be acquired by developing them.
The successful candidate will work at developing unsupervised machine learning methods for pattern discovery and detection in sequential data that are interpretable. The main application domain will be the speech signal, but other applications may be considered. The candidate may work in collaboration with the already established AULUS project.
We seek a highly-motivated individual who has
strong background in machine learning, signal processing and mathematics with research-oriented master thesis in a related field, e.g., statistical machine learning, statistical signal processing, speech technology, information theory, applied mathematics, or optimization
experience with programming
good written and oral English language skills
Publication activities in the aforementioned disciplines will be considered an advantage but is not a requirement.
For more information on the application submission and a detailed list of required documents, see subsection "About the application" below. The PhD-position's main objective is to qualify for work in research positions. The qualification requirement is completion of a master's degree or second degree (equivalent to 120 credits) with a strong academic background in Computer Science, Electrical Engineering, Computer Science, Applied Mathematics, or other relevant disciplines with a grade A or B in terms of NTNU's grading scale. Applicants with no letter grades from previous studies must have an equally good academic foundation. Applicants who are unable to meet these criteria may be considered only if they can document that they are particularly suitable candidates for education leading to a PhD degree.
The appointment is to be made in accordance with the regulations in force concerning State Employees and Civil Servants and national guidelines for appointment as PhD, post doctor and research assistant.
NTNU is committed to following evaluation criteria for research quality according to The San Francisco Declaration on Research Assessment - DORA.
The successful candidate should
- be creative, independent, and self-motivated
- possess good skills to deliver oral and written presentations of research results
In the evaluation of which candidate is best qualified, emphasis will be placed on education, experience and personal suitability, as well as motivation, in terms of the qualification requirements specified in the advertisement
Salary and conditions
PhD candidates are remunerated in code 1017, and are normally remunerated at gross from NOK 479 600 before tax per year. From the salary, 2 % is deducted as a contribution to the Norwegian Public Service Pension Fund.
The period of employment is 4 years with required duties. Appointment to a PhD position requires admission to the PhD programme in Electrical Engineering.
As a PhD candidate, you undertake to participate in an organized PhD programme during the employment period. A condition of appointment is that you are in fact qualified for admission to the PhD programme within three months.
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 criterias 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.
A good work environment is characterized by diversity. We encourage qualified candidates to apply, regardless of their gender, functional capacity or cultural background. Under the Freedom of Information Act (offentleglova), information about the applicant may be made public even if the applicant has requested not to have their name entered on the list of applicants.
Questions about the position can be directed to XXX, phone number XXX, e-mail XXX
About the application:
Publications and other academic works that the applicant would like to be considered in the evaluation must accompany the application. Joint works will be considered. If it is difficult to identify the individual applicant's contribution to joint works, the applicant must include a brief description of his or her contribution.
Please submit your application electronically via jobbnorge.no with your CV, diplomas and certificates. Applicants invited for interview must include certified copies of transcripts and reference letters. Please refer to the application number XXX when applying.
Application deadline: xx.xx.xx
Se annonsen og søk på stillingen www.jobbnorge.no PAM
Stillingsnummer: 5701-2019-09-93 (Oppgis ved kontakt med NAV)
Kilde: Overført fra PAM annonsemottak