Doctoral student in high-performance machine-learning aims at developing the principles behind the next generation of computing systems

KTH Royal Institute of Technology in Stockholm has grown to become one of Europe’s leading technical and engineering universities, as well as a key centre of intellectual talent and innovation. We are Sweden’s largest technical research and learning institution and home to students, researchers and faculty from around the world. Our research and education covers a wide area including natural sciences and all branches of engineering, as well as architecture, industrial management, urban planning, history and philosophy.

Project description

Third-cycle subject: Electrical Engineering

This research project aims at developing the principles behind the next generation of computing systems optimized for modern data-intensive workloads.  We believe that these systems will make a disruptive departure from the classic Von Neumann architecture, with its decoupling of memory and computing, and embrace the principle of processing-near-memory. In this way, it is possible to shortcut the main limitations of current hardware systems. Your role will be to explore how ML algorithms and computer architectures can be enhanced and radically re-designed for unprecedented efficiency and scalability.

The doctoral position is part of a multi-disciplinary research center on “Data-bound computing”, run by researchers with internationally leading expertise in algorithm development, distributed systems and computer architecture. This particular position is hosted by Professor Mikael Johansson’s research group at KTH, and you will collaborate with researchers and doctoral students at both KTH and Chalmers University. Together, we will take a holistic view of the computing hardware and algorithm pipelines and explore radically new computing architectures and algorithms, optimized for ML.

Supervision: The doctoral student will be supervised by Professor Mikael Johansson

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

We are looking for candidates with knowledge and background in applied mathematics and computer science. A suitable background is a master’s degree in Electrical engineering, Computer science, Technical physics, or Applied Mathematics. Experience from algorithm development for machine learning is desired.

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.

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.

https://youtube.com/watch?v=Sn2hApKmApI%3Frel%3D0
Type of employmentTemporary position longer than 6 months
Contract typeFull time
First day of employmentEnligt överenskommelse
SalaryMonthly salary according to KTH’s doctoral student salary agreement
Number of positions1
Working hours100%
CityStockholm
CountyStockholms län
CountrySweden
Reference numberJ-2022-1022
ContactFelicia Gustafsson, HR, rekrytering@eecs.kth.seProf. Mikael Johansson, mikaelj@kth.se
Published20.Apr.2022
Last application date31.May.2022 11:59 PM CEST

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