Doctoral student in Machine Learning for the Smart Grids - Hiring in process/Finished, not possible to apply

Project description

Third-cycle subject: Electrical engineering

With increasing economic or environmental concerns, advanced ICT technologies have been widely used in the power grid systems, especially when electrical production, selling and storage are more distributed. Thus, it is important to investigate how machine learning or edge computing can be used efficiently in smart grids. In the project, you will work on the research topic of artificial intelligence for smart grids, e.g., nano-grids or multi-layer systems. You will use recent development on machine learning, e.g., neural networks for analysis and prediction gird parameters. You are expected to use real data to predict the demanding or identify outage events in complex grids e.g., those with end-to-end selling or electrical vehicles. You will also establish a test bed for implementing theoretical algorithms. Background/degree on energy systems or/and machine learning is needed. Preferably, you should also know communication networks or edge computing. You will work on an European project with multiple partners.

The Division of Information Science and Engineering consists of faculty members, researchers and doctoral students (ca. 55 people in total) who contribute to a high professional standard of intensive work and quality results, as well as to a friendly and open environment. The staff has a multicultural background and the working language is English. The department is internationally well established, have many research collaborations with excellent partners worldwide, and are involved in several European and national projects. The excellent research environments at the department promote creativity and allow a lot of flexibility so that people can work in a way that fits best to them. The work commitment is very high and the cooperative setting creates a positive sense of belonging.

There are diverse backgrounds in the division, which will give you the opportunity to be trained in the areas of machine learning, communications, and optimization etc.

What we offer

• The possibility to study in a dynamic international research environment in close cooperation with industries and advanced universities the world over.
• Life-long network through KTH's Alumni organization.
• A personal study plan to support your development within your areas of interest.
• A workplace with many employee benefits and monthly salary according to KTH's doctoral student salary agreement.
• Work and study in Stockholm, one of Europe´s fastest growing capitals, which is close to both nature and the sea.
• Help to relocate and get settled in Sweden and at KTH.

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:

• passed a degree at advanced level,
• completed course requirements of at least 240 higher education credits, of which at least 60 higher education credits at advanced level, or
• in any other way acquired within or outside the country acquired essentially equivalent knowledge.

Selection

In order to succeed as an doctoral student at KTH you need to be goal oriented and persevering in your work. In the selection of the applicants, the following will be assessed:

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

The candidate should have a background/degree on energy systems and/or machine learning. Knowledge in communication networks and edge computing is meriting. Good command of English orally and in writing is required to publish and present results at international conferences and in international journals.

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 who are or have been admitted to third-cycle studies may be employed as a doctoral student. The term of the initial contract may not exceed one year and may thereafter be extended. Doctoral students may engage in teaching, research, and administration corresponding to a maximum of 20 % of a full-time position.

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)
• Copy of the degree certificate(s) and transcripts of records from your previously attended university-level institutions. Translations into English or Swedish if the original documents are not issued in one of these languages.
• Representative publications or technical reports. For longer documents, please provide a summary (abstract) and a web link to the full text.

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.

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