Doctoral student in learning and optimization for edge computing
10 hours ago
Doctoral student in learning and optimization for edge computing
Since its founding in 1827, KTH Royal Institute of Technology in Stockholm has grown to become one of Europe’s leading technical and engineering universities.
The Division of Network and Systems Engineering is looking for one doctoral student with a strong background and interest in system modeling, optimization, and machine learning. The successful candidate will join a MSCA Doctoral Network project on developing rigorous, novel tools for safe and prompt learning and optimization of distributed network infrastructures. A strong focus will lie on the development of algorithms that include machine learning components, and on cooperation with industrial partners and with the TECoSA competence center at KTH.
The Division conducts fundamental research in networked systems, wireless communications, and cyber security. Industrial projects involve partners such as Ericsson, Atlas Copco, and Telenor. Research is conducted within the framework of the Wallenberg AI, Autonomous Systems and Software Program and in Digital Futures. We collaborate with researchers at MIT, UIUC, Stanford, EPFL, among others.
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), or
- 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.
Applicants must not have resided or carried out their main activity (work, studies, etc.) in Sweden for more than 12 months in the 36 months immediately before the date of recruitment, due to the MSCA DN mobility rules. In addition, there is a mandatory requirement for English equivalent to English B/6.
Selection
In order to succeed as a doctoral student at KTH, you need to be goal-oriented and persevering in your work. Candidates will be assessed upon their ability to:
- Independently pursue their work,
- Collaborate with others,
- Maintain a professional approach, and
- Analyse and work with complex issues.
Great emphasis is placed on study results and completed courses. An earlier specialization in optimization, mathematical statistics, and/or machine learning is highly desirable.
Applicants are expected to be able to read and write scientific texts in English and communicate verbally in Swedish, as it is required in everyday work.
What we offer
- The possibility to study in a dynamic and international research environment in collaboration with industries and prominent universities from around the world.
- A workplace with many employee benefits and monthly salary according to KTH’s Doctoral student salary agreement.
- Help to relocate and settle in Sweden and at KTH.
Application process
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 by the closing date at midnight, CET/CEST.
Applications must include:
- CV including relevant professional experience and knowledge.
- Copies of diplomas and grades from previous university studies and certificates of fulfilled language requirements. 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.
Contact
Prof. György Dan, gyuri@kth.se
Prof. Viktoria Fodor, vjfodor@kth.se
HR Officer Lisa Olsson, rekrytering@eecs.kth.se
Important dates
Published: 2024-12-05
Last application date: 2025-02-14
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