Student Teaching Assistant @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 proved 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

  • Mainly, support of Teaching Staff (Lab queue Q&A sessions, Grading, Development of new exercises for courses @IDEA lab)
  • Secondary, support of Research @IDEA lab (minor projects related to image analysis - practical experience with FAU HPC is an advantage)


Notwendige Qualifikationen:

  • Profound knowledge in Computer Science, Medical Engineering or Electrical Engineering (or similar study programmes)
  • Profound (practical) knowledge in the programming language PYTHON (additional knowledge in JAVA is an advantage)
  • High motivation to support teaching staff and contribute to the chair's research work
  • Organised and independent way of working with focus on quality and accuracy
  • Very good communication skills in English
  • High ability to cooperate with an interdisciplinary team of researchers and other student research assistants

Wünschenswerte Qualifikationen:

  • Profound knowledge in Machine learning for potential research-related work @IDEA lab
  • if available, please provide a list of your public GitHub repositories in your CV
  • if available, please add an employer's reference or credentials

Ergänzende Beschreibung

Please send your cover letter, curriculum vitae, transcript of records and an ~100-word motivation letter with following subject line: STA2023WS. Applications with missing information will be considered incomplete and will not be processed. We are looking for potential student assistants who target a longer employment term than one semester, the ideal candidate would be in 2./3. master semester.

The Department AIBE and FAU sees 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.


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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".

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Veröffentlichungsdatum: 14.12.2022