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

Project description

Third-cycle subject: Electrical Engineering

Do you want to contribute to renewable energy and meanwhile learn advanced information technologies (e.g., recent machine learning schemes)? With increasing economic or environmental concerns, advanced ICT technologies have been widely used in the renewale energy systems (RES), i.e., smart buildings/community, in e.g., distributed electrical production, selling and storage. Thus, it is imporant to investiage how machine learning particually distributed machine learning such as federated learning and ADMM can be used efficiently in RES. In the project, you will work on the research topic of artificial intelligence for RES for smart building, e.g., energy pricing, load balance and storage etc. You will use recent development on machine learning, e.g., deep learning, federated learning, ADMM or reinforced learning for analysis and prediction gird parameters. Jointly with industrial partners, you are expected to use real data to predict the demanding or pricing, storage etc. You will also establish a testbed for implementing theoretical algorithms. 

Supervision: The doctoral student will be supervised by Associate Professor Ming Xiao

What we offer

• The possibility to study in a dynamic and international research environment in collaboration with industries and prominent universities from all over the world.Read more
• A workplace with many employee benefits and monthly salary according to KTH’s Doctoral student salary agreement.
• A postgraduate education at an institution that is active and supportive in matters pertaining to working conditions, gender equality and diversity as well as study environment.
• Work and study in Stockholm, close to nature and the water.
• Help to relocate and be settled in Sweden and at KTH.
• The project will be hosted by Division of Information Science and Engineering, EECS school. You have opportunities to take advanced Ph.D courses to improve your knowledge. The project is funded by FORMAS. We will collaborate with industries for project implementation.

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

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.

Background/degree on machine learning is needed. The candidate should have strong mathematical analysis capability/background. Knowledge of smart grids and programming skills is meriting. The candidate should have demonstrated capability of independently writing research articles in English.

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.
• 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.