« View All Jobs

PhD studentships in machine learning and computer vision

taekyun999 – Posted on December 11, 2017 at 1:08 pm –

  • Job Type: PhD
  • Employer: Imperial College London
  • Location: South Kensington, London
  • Link: https://labicvl.github.io/
  • Job Descriptions:

Imperial College London is a
science-based institution with the greatest concentration of high-impact
research of any major UK university.  The
Faculty of Engineering, consistently rated among the best in the world, is made
up of 10 academic departments and is committed to increasing its research
activity by focusing on engineering-led multidisciplinary growth areas that
target a number of global challenges. All of our academic departments are
located on a single campus in South Kensington, giving a concentration of
talent that creates a stimulating and vibrant research community. You can find
out more about our staff benefits, including generous annual leave entitlements
and our excellent professional development opportunities, here: http://www.imperial.ac.uk/job-applicants/staff-benefits/.

Applications are invited for (x2) fully funded PhD studentships within the computer vision and learning lab (https://labicvl.github.io/)
that belongs to the Intelligent Systems and Networks Research Group (http://www3.imperial.ac.uk/intellisysnetworks), Department of Electrical and Electronic Engineering, Imperial College
London. The position is available under the supervision of Dr Tae-Kyun Kim. The funding covers up tuition fees at the Home/EU rate, and living cost. Internships prior to PhD commencement 
might be offered.  

The project focuses
on machine (deep) learning and computer vision, with applications in pose estimation and
detection/tracking. 
Applicants
will hold a MSc (or equivalent)
 with a solid academic background. Experience in the relevant  topics, deep learning, real-time vision algorithms, etc is preferred.

Good programming and demonstrative skills are required.

Enquires may be sent to Dr Tae-Kyun
Kim (tk.kim@imperial.ac.uk).


k();} ?>