School of Electrical Engineering and Computer Science at KTH

Project description

Third-cycle subject: Electrical engineering

The Division of Information Science and Engineering at the School of Electrical Engineering and Computer Science is currently looking for a doctoral student with a very strong background and interest in machine learning, statistical learning theory, information theory, and related topics. The goal of this project is to develop new principles and methods for training and analyzing machine learning algorithms and models in order to establish a better understanding of their generalization performance and to improve their robustness. Solutions and tools developed in this project will rest on a solid theoretical foundation and their good performance will be demonstrated and validated experimentally for practically relevant use-cases.

The Division of Information Science and Engineering conducts research and education on various aspects of information processing, learning, and communications. A major part of our research is conducted in collaboration with industrial and societal partners like Ericsson, Scania, SAAB, and Region Stockholm including the Karolinska University Hospital in Stockholm.

Supervision: Associate Professor Ragnar Thobaben is proposed to supervise the doctoral student. Decisions are made on admission

What we offer

Admission requirements

To be admitted to postgraduate education (Chapter 7, 39 § Swedish Higher Education Ordinance), the applicant must have basic eligibility in accordance with either of the following:

  • passed a second cycle degree (for example a master's degree),
  • completed course requirements of at least 240 higher education credits, of which at least 60 second-cycle higher education credits, or
  • acquired, in some other way within or outside the country, substantially equivalent knowledge

In addition to the above, there is also a mandatory requirement for English equivalent to English B/6, read more here

Selection

In order to succeed as a doctoral student at KTH you need to be goal oriented and persevering in your work. During the selection process, candidates will be assessed upon their ability to:

  • independently pursue his or her work
  • collaborate with others,
  • have a professional approach and
  • analyse and work with complex issues.

In the evaluation of candidates, great emphasis is placed on study results and completed courses. An earlier specialization in theoretical aspects of machine learning, statistical learning theory, information theory, signal processing, and/or mathematics is highly desirable and especially meritorious. Related programming skills including Python are required. Early engagement with the research community and experience from other projects is a plus.

After the qualification requirements, great emphasis will be placed on personal competency. 

Target degree: Doctoral degree

Information regarding admission and employment

Only those admitted to postgraduate education may be employed as a doctoral student. The total length of employment may not be longer than what corresponds to full-time doctoral education in four years ' time. An employed doctoral student can, to a limited extent (maximum 20%), perform certain tasks within their role, e.g. training and administration. A new position as a doctoral student is for a maximum of one year, and then the employment may be renewed for a maximum of two years at a time.

Union representatives

You will find contact information for union representatives on KTH's website.

Doctoral section (Students’ union on KTH Royal Institute of Technology)

You will find contact information for doctoral section on the section's website.

Application

Apply for the position and admission through KTH's recruitment system. It is the applicant’s responsibility to ensure that the application is complete in accordance with the instructions in the advertisement.

Applications must be received at the last closing date at midnight, CET/CEST (Central European Time/entral European Summer Time).

Applications must include the following elements:

  • CV including your relevant professional experience and knowledge.
  • Application letter with a brief description of why you want to pursue research studies, about what your academic interests are and how they relate to your previous studies and future goals. (Maximum 2 pages long)
  • Copies of diplomas and grades from previous university studies and certificates of fulfilled language requirements (see above). Translations into English or Swedish if the original document is not issued in one of these languages.Copies of originals must be certified.
  • Representative publications or technical reports. For longer documents, please provide a summary (abstract) and a web link to the full text.

Other information

Striving towards gender equality, diversity and equal conditions is both a question of quality for KTH and a given part of our values.

For information about processing of personal data in the recruitment process please read here.

We firmly decline all contact with staffing and recruitment agencies and job ad salespersons.

Disclaimer: In case of discrepancy between the Swedish original and the English translation of the job announcement, the Swedish version takes precedence.

 

 

Type of employment Temporary position
Contract type Full time
First day of employment According to agreement
Salary Monthly salary according to KTH's doctoral student salary agreement
Number of positions 1
Full-time equivalent 100%
City Stockholm
County Stockholms län
Country Sweden
Reference number J-2022-0772
Contact
  • Ragnar Thobaben, Universitetslektor, ragnart@kth.se
  • Anna Mård, HR-handläggare, rekrytering@eecs.kth.se
Published 07.Apr.2022
Last application date 06.May.2022 11:59 PM CEST

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