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Faculty of Information Technology and Electrical Engineering
Department of Mathematical Sciences

PhD fellowship in Statistical Learning

About the research project

A new PhD fellowship in statistical learning is available in the Statistics group at the Department of Mathematical Sciences (IMF), NTNU. The successful candidate will be offered a three-year position. The Department may offer a six to twelve months extension as a teaching assistant.

 

In the intersection between machine learning, data mining and statistics, we find statistical learning. Statistical learning aims at providing accurate and reliable predictions in large data sets from real life applications. Understanding how and why the methods work on a particular data set can lead to the development of improved methods, and this is the major aim of the PhD fellowship. Models and methods from probability theory, statistical inference and computational statistics are key elements to arrive at this goal, and the successful applicant has experience from working with multivariate statistical models and methods and good programming skills. Possible application areas will be sensor systems, neuroscience, genomics, energy and environmental sciences.

 

The specific methodological focus of the PhD fellowship within statistical learning will be decided in cooperation with a supervisor in the statistics group, co-supervisors in collaborating groups and departments at the Faculty/NTNU (such as the Telenor-NTNU AI-Lab), and the PhD candidate.

 

Qualifications

The applicant must have a master’s degree in statistics or comparable competence, and must also satisfy the requirements for admission to the PhD education NTNU; please see https://www.ntnu.edu/phd and https://www.ntnu.edu/studies/phma. In particular, admission to PhD education at NTNU requires an average grade of at least B, within a scale of A-E for passing grades (A best), for the last two years of the master’s degree.

 

Students who expect to complete their master’s degree studies by the summer of 2018 are encouraged to apply. Employment will then be postponed until the master’s degree is finished.

 

The applicants who do not master a Scandinavian language must document a thorough knowledge of English (equivalent to a TOEFL score of 600 or more).

 

The application

Applications are to be submitted electronically through this page. Preferably, the attachments should be submitted as a single file. Only applications what include the following will be evaluated:

  • Information about educational background and work experience.
  • Relevant publications. Joint work will only be considered provided that a short summary outlining the applicant's contributions is attached.
  • Certified copies of relevant transcripts and diplomas. Candidates from universities outside Norway are kindly requested to send a Diploma Supplement or similar documentation, which describes in detail the programme of study, the grading system, and the rights to further studies associated with the degree obtained.
  • Contact information for two references.
  • An essay (around 600 words) with the title “Experiences from my master’s thesis that will be relevant for working with statistical learning”. Candidates who have not finished their master’s thesis can alternatively write about a project they have worked on during their studies (bachelor or 5th year project).

The following will be emphasized in the evaluation of the applications:

  • Interest in programming, and good knowledge of R or Python or MATLAB.
  • Interest in computational aspects of statistics, and in particular multivariate modelling and analysis.
  • Interest in working with data from real life applications.
  • Good communication skills and interest in working in a multidisciplinary environment.
  • Written fluency in the English language.

Terms of employment

The PhD fellow will be part of the Department of Mathematical Sciences at NTNU and will have her/his workplace there. See https://www.ntnu.no/imf. The Department currently has around 60 PhD fellows.

 

The PhD fellowship is placed in salary code 1017, with a gross salary of NOK 436 500 per year before tax. A pension contribution of 2% of the salary will be deducted as an obligatory premium to the Norwegian Public Service Pension Fund.


The appointment of the PhD fellow will be made according to Norwegian guidelines for universities and university colleges and to the general regulations regarding university employees. Applicants must agree to participate in organized doctoral study programmes within the period of the appointment and have to be qualified for the PhD-study
(see http://www.ntnu.edu/ime/research/phd ).


The successful candidate will be required to enroll in a PhD programme within the period of employment, and must sign a contract regulating the starting date and duration of employment as well as the required duties.

 

The position adheres to the Norwegian Government’s policy of balanced ethnicity, age and gender. NTNU wishes to increase the number of women in its workforce, and female candidates are therefore encouraged to apply.

 

For further information, please contact:

Mette Langaas, Mette.Langaas@ntnu.no .

Jo Eidsvik, Jo.Eidsvik@ntnu.no .

 

Reference no: IE 128-2017.        

 

Closing date: 31.01.2018.

Søk stillingen

Om stillingen

  • Søknadsfrist
    31. januar 2018
  • Arbeidsgiver
    NTNU - Norwegian University of Science and Technology
  • Nettside
  • Kommune
    Trondheim
  • Arbeidssted
    Trondheim
  • Jobbnorge-ID
    145483
  • Intern-ID
    IE 128-2017
  • Omfang
    Heltid
  • Varighet
    Prosjekt

Om søknader

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