This advert is not available!
Project description
Third-cycle subject: Electrical Engineering
We are looking for a doctoral student to join our efforts in developing theory for advanced machine learning within the research project "The mathematics of scalable optimization: asynchrony, adaption and information".
Optimization is the algorithmic workhorse of a lot of modern AI and machine learning. Increasingly often, learning and decision tasks are formulated, analyzed and solved as large-scale optimization problems. As these problems grow in size (for example, due to increasing amounts of data or a desire to coordinate ever more decisions) existing algorithms struggle to find a sufficiently good solution within a short time. This research project aims at developing fundamental theory and algorithms for which are able to solve large-scale optimization problem at an unprecedented speed, eventually supporting decision-making in real-time.
The research project is part of the Wallenberg AI, Autonomous Systems and Software Program.
Supervision: The doctoral student will be supervised by: Mikael Johansson
What we offer
Eligibility
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:
Good command of English orally and in writing is required to publish and present results at international conferences and in international journals.
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 assed upon their ability to:
We are looking for candidates with very strong background in applied mathematics. Experience from algorithm development and machine learning is an asset. Succesful candidates should be analytical, have excellent academic merits and a passion for research.
After the qualification requirements, great emphasis will be placed on personal qualities and personal suitability.
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:
Other information
Gender equality, diversity and zero tolerance against discrimination and harassment are important aspects of KTH's work with quality as well as core values in our organization.
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 | May, 2020 |
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-2020-0346 |
Contact |
|
Published | 13.Feb.2020 |
Last application date | 15.Mar.2020 |