School of Engineering Sciences in Chemistry, Biotechnology and Health at KTH

Project description

Structural brain connectivity estimates the degree of connectivity among regions in the cortex by analyzing the distribution of neural fibers in the white matter. The current tools for brain connectivity are not accurate enough for clinical use. In this project, we aim to close this gap by proposing new advanced artificial intelligence (AI)-based tools for performing structural brain connectivity analysis. For this, we will use advanced magnetic resonance imaging (MRI) sequences, including diffusion MRI (dMRI), multidimensional dMRI (MD-dMRI), and MR elastography (MRE). In collaboration with researchers at Karolinska Institute (KI), we will test the effectiveness of the tools to answer clinically relevant questions for Alzheimer’s disease, multiple sclerosis, and normal aging. This project is funded by the Swedish Research Council.

Third-cycle subject: TH Technology and Health

Supervision: Rodrigo Moreno is proposed to supervise the doctoral student. Decisions are made on admission

What we offer

  • The possibility to study in a 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 and monthly salary according to KTH’s Doctoral student salary agreement.
  • A postgraduate education at an institution that is active and supportive in matters pertaining to working conditions, gender equality and diversity as well as study environment.
  • Work and study in Stockholm, close to nature and the water.
  • Help to relocate and be settled in Sweden and at KTH.
  • A research group with high competence in advanced machine learning for medical imaging applications.
  • A cross-disciplinary academic environment with close collaboration between technical researchers from KTH and clinical researchers from Karolinska Institute (KI)

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
  • Experience in image analysis and deep learning is required.
  • Good programming skills are required.
  • In addition to the above, there is also a mandatory requirement 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
  • analyse and work with complex issues.
  • Good oral and written communication skills in English.
  • Strong background in mathematics or physics is not required, but it is highly recognized as a merit.
  • Experience with PyTorch or TensorFlow is meritorious

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

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/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.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 please read here.

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 According to 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 C-2023-0257
Contact
  • Rodrigo Moreno, +468799787
Published 09.Feb.2023
Last application date 09.Mar.2023 11:59 PM CET

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