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PhD Candidate Within Machine Learning

Employer
NORWEGIAN UNIVERSITY OF SCIENCE & TECHNOLOGY - NTNU
Location
Trondheim, Norway
Closing date
10 Dec 2019

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Academic Discipline
Computer Science, Engineering & Technology
Job Type
Academic Posts, Postdocs
Contract Type
Temporary
Hours
Full Time

About the position

The Faculty of Information Technology and Electrical Engineering at the Norwegian University of Science and Technology (NTNU) has a vacancy for a Computer Science PhD fellowships at the Department of Computer Science (IDI). The positions will do research on machine learning, data science, and artificial intelligence for large-scale and structural data. The appointment is for 4 years with 25% teaching duties or 3 years without.

The positions are funded by Norwegian Open AI Lab (NAIL) and the Norwegian Research Council ShuttleNet project, both hosted by NTNU IDI. NAIL is a research center bringing together research, education and innovation within AI, with objectives to enable both basic and applied interdisciplinary research at high international level, and to foster strong partnerships between academia, the private sector, public sector, and research institutes.

The position reports to Head of department.

Main duties and responsibilities

The PhD candidates will be supervised by Prof. Zhirong Yang. The candidates will mainly perform research on next-generation deep neural networks, which can significantly improve inference for large-scale structured data such as DNA sequence, text corpus, time series, as well as networked and graphical data. The research findings can be applied to various domains, including telecommunication, biology, natural language understanding, human computer interaction, etc. The research and development will mainly take place in NTNU IDI in Trondheim, Norway. The candidates will also participate in other relevant research activities through our collaborators worldwide.

Qualification requirements

PhD candidate:

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 or equivalent education with a grade of B or better 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 applicants should have a solid background in machine learning, especially in deep learning
  • A research-oriented master thesis within machine learning is required
  • Good programming skills are required
  • Strong mathematical skills are necessary in the project
  • Good written and oral English skills. Applicants 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
  • In extraordinary circumstances, formal documentation of language skills can be relinquished. In such cases the candidate’s language skills will be assessed in a personal inteIrview

Other qualifications (applicants with the following qualifications will be prioritized)

  • Experience in sequential modeling in for example natural language processing, time series, and DNA sequences
  • distributed programming experience, for instance, in CUDA development

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, postdoctor and research assistant

NTNU is committed to following evaluation criteria for research quality according to The San Francisco Declaration on Research Assessment - DORA.

Personal characteristics

  • Ability to work and think independently
  • Enthusiasm and passion
  • Perseverance and commitment

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

We offer

Salary and conditions

PhD candidate:

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 or 3 years without required duties. Appointment to a PhD position requires admission to the PhD programme in [subject area] (Link to website, if applicable). 

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.

General information

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.

The national labour force must reflect the composition of the population to the greatest possible extent, NTNU wants to increase the proportion of women in its scientific posts. Women are encouraged to apply. Furthermore, Trondheim offers great opportunities for education (including international schools) and possibilities to enjoy nature, culture and family life (http://trondheim.com/). Having a population of 200 000, Trondheim is a small city by international standards with low crime rates and little pollution. It also has easy access to a beautiful countryside with mountains and a dramatic coastline.

Questions about the positions can be directed to Prof. Zhirong Yang, phone number +47-90154911, e-mail zhirong.yang@ntnu.no

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. Applications submitted elsewhere will not be considered. Diploma Supplement is required to attach for European Master Diplomas outside Norway. Chinese applicants are required to provide confirmation of Master Diploma from China Credentials Verification (CHSI): http://www.chsi.com.cn/en/).

The application must contain the following:

  • Curriculum vitae (CV) with information about the candidate’s prior training, exams, and work experience
  • Certified copies of transcripts and diplomas for the whole bachelor and master’s degree. An English translation of all education documents is required unless the documents are in Norwegian
  • Applicants from universities outside Norway are kindly requested to send a diploma supplement or a similar document that describes in detail the study and grading system and the rights for further studies associated with the obtained degree
  • Research statement (max. 4 pages) including:
    • A short presentation of the motivation for a PhD study
    • How the applicant sees his/her background suitable
    • The applicant’s view of research challenges within machine learning, in particular, how to perform inference on long sequential data such as text, speech, DNA, and time series.
    • How the competence of the applicant can contribute to solving these challenges
    • A proposed research plan including appropriate research methods and what theories could be relevant to examine the topic of AI and business value
    • Names and contact information of at least 2 reference persons
  • A copy of the master thesis (in PDF), or, for those who are near to completion of their MSc, an extended abstract combined with a statement of how and when the applicant plans to complete the thesis
  • Attachments of any other relevant documents (e.g. certificates, diplomas, publications)

Incomplete applications will not be considered.

Applicants invited for interview must include certified copies of transcripts and reference letters.

Please refer to the application number 2019/37729 when applying.

Application deadline: 10.12.2019

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 Science is one of seven departments in the Faculty of Information Technology and Electrical Engineering .

Deadline 10th December 2019
Employer NTNU - Norwegian University of Science and Technology
Municipality Trondheim
Scope Fulltime
Duration Temporary
Place of service Trondheim

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