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 evidenced by 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

We offer informatics-focused master's theses in cooperation with the University Hospital Erlangen (UKER). One topic is based on the exploration and implementation of a Kaapana test setup for prototyping applications for fast diagnosis tools with the help of AI /ML. The second topic is centred around backend development by exploring Kubeflow for ML workflows. The thesis tasks can be customised to match the candidate's interests and expertise. Please contact Müller, Johanna for further details.

Qualifikationen

Notwendige Qualifikationen:

  • Profound knowledge in Computer Science, Medical Engineering or Electrical Engineering (M.Sc. study programmes)
  • Profound (practical) knowledge of the programming language Python
  • Profound (practical) knowledge of open-source container orchestration systems, e.g., Docker and Kubernetes
  • Profound (knowledge of Machine learning/AI algorithms)
  • 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 open-source workflow management platforms for data engineering pipelines, e.g., Apache Airflow
  • High ability to cooperate within an interdisciplinary team of researchers
  • 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.

Anmerkung

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Veröffentlichungsdatum: 08.01.2024