Master's Thesis @IDEA Lab

The successful applicant will be part of the Image Data Exploration and Analysis (IDEA) lab @AIBE FAU, which is the research group of Prof. Bernhard Kainz. We have pioneered new methodological developments in the field of medical image analysis and machine learning as evident from several international awards, prizes, and best paper awards. The group is internationally renowned for its research in medical deep learning, which has been proven by publications at top conferences (MICCAI, CVPR, ECCV) and in prestigious journals (IEEE TMI, Medical Image Analysis, npj Nature Digital Health, The Lancet, etc.).

Das Aufgabengebiet umfasst

MRI reconstructions pose significant challenges in terms of speed and accuracy. The process involves transforming raw data into detailed images, requiring advanced algorithms and computational power. The trade-off between reconstruction time and image quality is critical, as faster reconstructions may sacrifice the precision of diagnostic information. Additionally, advancements in machine learning and deep learning techniques are being explored to enhance the efficiency and reliability of MRI reconstructions.

This thesis aims to develop a platform demo including integrating an already existing DL backend, developing a User Interface and systems engineering/programming. Background in MRI reconstruction is helpful but not absolutely necessary.


Notwendige Qualifikationen:

  • Profound knowledge in Computer Science, Medical Engineering or Electrical Engineering (or similar study programmes)
  • Profound (practical) knowledge of User Interface (UI) Programming
  • Profound (practical) knowledge of the programming language Python/C++
  • Profound (practical) knowledge of Systems Programming/Engineering
  • High motivation and high interest in the described topic
  • Organised and independent way of working with a focus on quality and accuracy
  • Very good communication skills in English

Wünschenswerte Qualifikationen:

  • Profound (practical) knowledge of advanced compiler environments
  • Profound (practical) knowledge of User Experience (UX) Design
  • if available, please provide a list of your public GitHub repositories in your CV
  • if available, please add an employer's reference or credentials
  • if possible, please add the transcripts of records from FAU study programme

Ergänzende Beschreibung

Befristetes Forschungsvorhaben

Applications with missing information will be considered incomplete and will not be processed. Kindly refrain from sending emails regarding application status, we will contact only the successful applicant for this position.

The Department AIBE and FAU see itself as a progressive and forward-thinking employer. We welcome your application regardless of your age, gender, cultural and social background, religion, belief, disability or sexual identity. Friedrich Alexander University promotes professional equality for minority groups and women. These groups are therefore expressly encouraged to apply. Severely disabled persons within the meaning of the Severely Disabled Persons Act will be given preferential consideration in the case of equal professional qualifications and personal suitability if the advertised position is suitable for severely disabled persons. At the applicant's request, the Equal Opportunity Officer may be called in for the interview without any disadvantage to the applicant.


Für alle Stellenausschreibungen gilt: Die Friedrich-Alexander-Universität fördert die berufliche Gleichstellung der Frauen. Frauen werden deshalb ausdrücklich aufgefordert, sich zu bewerben.

Schwerbehinderte im Sinne des Schwerbehindertengesetzes werden bei gleicher fachlicher Qualifikation und persönlicher Eignung bevorzugt berücksichtigt, wenn die ausgeschriebene Stelle sich für Schwerbehinderte eignet. Details dazu finden Sie in der jeweiligen Ausschreibung unter dem Punkt "Bemerkungen".

Bei Wunsch der Bewerberin, des Bewerbers, kann die Gleichstellungsbeauftragte zum Bewerbungsgespräch hinzugezogen werden, ohne dass der Bewerberin, dem Bewerber dadurch Nachteile entstehen.

Ausgeschriebene Stellen sind grundsätzlich teilzeitfähig, es sei denn, im Ausschreibungstext erfolgt ein anderweitiger Hinweis.

Veröffentlichungsdatum: 09.01.2024