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Third-cycle subject: Electrical Engineering
Machine learning for limited data systems: There are many application scenarios where data is not in abundance. Data is limited and the systems / scenarios cannot be excited to generate more data to teach machine learning algorithms. For example, machine learning for detection of rare disease from images, or modeling a robot’s fall or decisions based on an upcoming car crash. Therefore, it is important to combine model-driven signal processing and data-driven machine learning for efficient engineering solutions. This PhD project is dedicated to such data-limited applications.
The PhD position is in the Division of Information Science and Engineering (ISE), School of Electrical Engineering and Computer Science (EECS), KTH. The ISE division consists of faculty members, researchers and doctoral students 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. More information about the division can be found in https://www.kth.se/ise/
Supervision: The doctoral student will be supervised by: Saikat Chatterjee
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:
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:
The successful applicant should have an outstanding academic track record, and well-developed analytical and problem solving skills including programming skills to develop data analytics platforms. We are looking for a strongly motivated person, who is able to work independently. 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.
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.
You will find contact information for union representatives on KTH's website.
You will find contact information for doctoral section on the section's website.
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:
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.
Type of employment | Temporary position |
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Contract type | Full time |
First day of employment | According to agreement |
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-2020-1711 |
Contact |
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Published | 10.Sep.2020 |
Last application date | 30.Sep.2020 |