Connectionists: [Job] PhD in Deep Learning, KTH Royal Institute of Technology

[Kevin Smith]

Please see the full job ad and application form here:
https://www.kth.se/en/om/work-at-kth/lediga-jobb/what:job/jobID:253724/where:4/

Project description

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.

The research will be conducted at the School for Electrical Engineering and
Computer Science (EECS), under the supervision of Assistant Professor Kevin
Smith (https://www.kth.se/profile/ksmith) whose main focus is on computer
vision and biomedical image analysis.

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.

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.
   -

   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 Linux
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