KTH Royal Institute of Technology,EECS

Project description

Third-cycle subject: Computer Science

The successful applicants will be expected to work in the area of deformable object manipulation. When manipulating highly deformable objects such as cloths, one of the main challenges is the difficulty of modeling the object's dynamical behavior, which makes it difficult to apply traditional control-based methods. The difficulty also lies in high amounts of uncertainty, complex physics, and high dimensionality of state spaces. On the other hand, such objects are also usually hard to reliably simulate, which makes it challenging to directly apply learning-based methods that rely on high amounts of
training data.

Therefore, we believe that there is a need for novel methods and efficient object representations that would combine the strengths of Control-based and Reinforcement Learning-based techniques in order to provide data-efficient solutions for complex tasks involving highly deformable objects. The focus of this project will, therefore, be on analyzing noisy and incomplete input data coming from different sensor modalities, such as depths cameras, force, and torque sensors, etc, and representing it efficiently to enable reliable control strategies for real-world applications.

We offer two positions that will focus on either Control and Reinforcement Learning, or Perception of deformable object manipulation. 

Supervision: The doctoral student will be supervised by Professor Danica Kragic.

What we offer

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 an advanced level,
  • completed course requirements of at least 240 higher education credits, of which at least 60 higher education credits at an 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 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
  • analyze and work with complex issues.

For the position that focuses on Control and Reinforcement Learning the applicant needs:

  • A theoretical understanding of Control Theory
  • Good programming skills in C++ and Python
  • Proficiency in Machine Learning methods
  • Experience with real robotic system is preferred

For the position that focuses on Perception the applicant needs:

  • Expertise in Machine Learning and Optimization methods
  • Good programming skills in C++ and Python
  • Proficiency in Computer Vision is preferred

After the 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

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/central 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 the 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 a discrepancy between the Swedish original and the English translation of the job announcement, the Swedish version takes precedence.

Type of employment Temporary position
Contract type Full time
First day of employment In agreement with supervisor
Salary Monthly salary according to KTH's doctoral student salary agreement
Number of positions 2
Full-time equivalent 100%
City Stockholm
County Stockholms län
Country Sweden
Reference number J-2020-1171
Contact
  • Professor Danica Kragic, dani@kth.se
  • Sarah Kullgren, HR Officer, sarahku@kth.se
Published 11.Jun.2020
Last application date 10.Aug.2020 11:59 PM CEST

Return to job vacancies