Doctoral student in deep learning

Kungliga Tekniska högskolan, School of Electrical Engineering and Computer Science

Project description

The research will be conducted at the Science for Life Laboratory ( www.scilifelab.se ) as part of the Division of Computational Science and Technology, under the supervision of Associate Professor Kevin Smith whose main focus is on computer vision and biomedical image analysis.

Deep learning has dramatically pushed the performance of many intelligent systems, but many important questions remain open for research. How can we make sense of the high capacity of deep networks? How should one interpret its decision making process? How can we transfer knowledge from an information-rich application to tasks where data is scarce? What are the limits of its application in other fields? The role of the doctoral student will be to develop theoretical advances regarding these research questions and focus on applying them to problems in computer vision and/or biomedical image analysis. Possible topics of interest include: knowledge transfer, universal representation and learning, understanding deep networks, explainability, and uncertainty estimation. Should the student be willing and sufficiently experienced, they will have some freedom to steer the direction of research.

Please include with your application a short (1 page) project proposal describing a topic around deep learning and/or biomedical image analysis that you would like to pursue in your doctoral studies.

Third-cycle subject:Computer Science

Supervision: The doctoral student will be supervised by Associate Professor Kevin Smith

What we offer

  • Possibility to study in 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 ,monthly salary KTH s Doctoral student salary agreement.
  • A postgraduate education at institution,active and supportive in matters pertaining to working conditions, gender equality, diversity and study environment.
  • Help to relocate and be settled in Sweden and at KTH
  • Access to state-of-the-art computational resources for deep learning

Eligibility

To be admitted to postgraduate education (Chapter 7, 39 Swedish Higher Education Ordinance)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
  • Requirements 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 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
  • Good knowledge of English and ability to express themselves clearly in speech and writing
  • Motivation for doctoral studies
  • Mathematical skillset
  • Experience in use of deep learning frameworks including TensorFlow, PyTorch, Keras, Caffe, MXNet, etc as well as familiarity with LinuxSelection

After qualification requirements, great emphasis will be placed on personal qualities and personal suitability

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

Contact information for union representatives on KTH's website .

Contact information for doctoral section on the section's website .

Application

Apply for position and admission through KTH's recruitment system. It is applicant s responsibility to ensure that application is complete in accordance with the instructions in 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

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.

We decline contact with staffing/recruitment agencies, 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.

Type of employment: Temporary position longer than 6 months
Working hours: Full time
Salary: Monthly salary according to kth's doctoral student salary agreement
City: Stockholm
Reference number: J-2020-1775
Published: 2020-09-10
Last application date: 2020-10-08


Company

Kungliga Tekniska högskolan

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