School of Electrical Engineering and Computer Science at KTH

Project description

Third-cycle subject: Electrical Engineering

WELD-AID is a Vinnova-funded project that aims to revolutionize quality assurance in welded structures by integrating Artificial Intelligence (AI) and digitalization. Through collaboration with industry partners, it seeks to reinforce Sweden as a global leader in designing and manufacturing welded products, ensuring superior mechanical performance and production quality. The project will explore using advanced machine learning (ML) methods, including deep neural networks (DNNs), to detect weld imperfections and optimize the welding process. Within the grander research project, the advertised doctoral student position will develop hybrid models involving convolutional neural networks (CNNs) for weld localization and use physics-informed neural networks (PINN) for weld quality assessment, including service life predictions for welded structures.

Supervision: Professor Joakim Jaldén (Division of Information Science and Engineering) will be the main doctoral supervisor, with support from Professor Zuheir Barsoum (Division of Material and Structural Mechanics) as co-supervisor.

What we offer

Admission requirements

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 second cycle degree (for example a master's degree), or
  • completed course requirements of at least 240 higher education credits, of which at least 60 second-cycle higher education credits, or
  • acquired, in some other way within or outside the country, substantially equivalent knowledge

In addition to the above, there is also a mandatory requirement for English equivalent to English B/6.

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
  • analyse and work with complex issues.

A successful candidate should have documented good practical and theoretical knowledge of state-of-the-art machine learning methods including deep neural networks and be a proficient programmer, particularly in Python whereas knowledge of lower-level programming languages (C/C++, Cuda) will be considered meritorious.

Knowledge of structural mechanics or materials science is not required (for this particular doctoral position) but will also be considered a merit.

It is advantageous if the candidate can express him- or herself well in Swedish in speech and writing, as this facilitates cooperation with the Swedish industry.

After the qualification requirements, great emphasis will be placed on personal skills. 

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.

Doctoral section (Students’ union on KTH Royal Institute of Technology)

Contact information for doctoral section.

To apply for the position

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.
  • 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. Copies of originals must be certified.
  • Representative publications or technical reports. For longer documents, please provide a summary (abstract) and a web link to the full text.

Other information

Striving towards gender equality, diversity and equal conditions is both a question of quality for KTH and a given part of our values.

For information about processing of personal data in the recruitment process.

According to The Protective Security Act (2018-585), the candidate must undergo and pass security vetting if the position is placed in a security class. Information regarding whether the position is subject to such a classification will be provided during the recruitment process.

We firmly decline all contact with staffing and recruitment agencies and 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
Contract type Full time
First day of employment By 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-2024-2148
Contact
  • Prof. Joakim Jaldén, jalden@kth.se
  • HR Viktor Söderlund, rekrytering@eecs.kth.se
Published 05.Sep.2024
Last application date 01.Nov.2024 11:59 PM CET

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