PhD Candidate in learning and optimization for edge computing | |
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Workplace | Stockholm, Södermanland, Sweden |
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Position | |
School of Electrical Engineering and Computer Science at KTHProject descriptionThird-cycle subject: Computer science The Division of Network and Systems Engineering is looking for one doctoral students with a very 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 of Network and Systems Engineering conducts fundamental research in networked systems, wireless communications and cyber security. Industrial projects involve partners such as Ericsson, Atlas Copco and Telenor. Part of the research is conducted within the framework of the Wallenberg AI, Autonomous Systems and Software Program and in Digital Futures . We have an extensive academic network and collaborate with researchers at MIT, UIUC, Stanford, EPFL, among others. For more information Supervision: Prof. Viktoria Fodor and Prof. György Dán What we offer
Admission requirementsTo 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:
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 to the above, there is also a mandatory requirement for English equivalent to English B/6. SelectionIn 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:
In the evaluation of candidates, great emphasis is placed on study results and completed courses. An earlier specialization in optimization and/or mathematical statistics and/or machine learning is highly desirable and especially meritorious. Applicants are expected to be able to read and write scientific texts in English, as well as being able to communicate verbally in Swedish, as it is demanded in the everyday work. After the qualification requirements, great emphasis will be placed on personal competency. Target degree: Doctoral degree Information regarding admission and employmentOnly 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. In the case of studies that are to be completed with a licentiate degree, the total period of employment may not be longer than what corresponds to full-time doctoral education for two years. Union representativesYou 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 . To apply for the positionApply 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/Central European Summer Time). Applications must include:
Other informationStriving 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. According to The Protective Security Act (2018-585), the candidate must undergo and pass security vetting if the position is placed in a security class. Information regarding whether the position is subject to such a classification will be provided during the recruitment process. We firmly decline all contact with staffing, 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.
About KTHKTH 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. Read more here Apply here Type of employment Temporary position Contract type Full time Full-time equivalent 100% First day of employment According to agreement Salary Monthly salary according to KTH's doctoral student salary agreement Number of positions 1 Location Stockholm County Stockholms län Country Sweden Reference number J-2024-3234 Published 05.Dec.2024 Last application date 03.Feb.2025 Contact Prof. György Dan gyurikth.se Prof. Viktoria Fodor vjfodorkth.se HR Officer Lisa Olsson rekryteringeecs.kth.se | |
In your application, please refer to myScience.org and reference JobID 3011218. |
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