Benutzerspezifische Werkzeuge

Postdoc - Applied Deep Learning for Biomedical Data (f/m/x)

The Institute for Medical Informatics and Biometry (chair: Prof. Dr. Ingo Roeder) at the Faculty of Medicine Carl Gustav Carus, Technische Universität Dresden, Germany, is seeking a highly motivated

Postdoc - Applied Deep Learning for Biomedical Data (f/m/x)

(Full-time, limited for two years, with potential for extension)

The postdoc will develop, implement and apply deep learning and other innovative machine learning techniques to analyze biomedical data, such as images, time courses or single-cell sequencing data. Our institute is specifically interested to strengthen our core research areas in the field of hematology and oncology. The research focus should connect to and complement our bioinformatics and modeling efforts in those fields and further intensify collaborations with clinical partners at our faculty, the University Hospital Carl Gustav Carus and the National Center for Tumor Diseases Dresden. The Postdoc will also be engaged in teaching activities, e. g. within the Master Program "Computational Modeling and Simulation". Previous experiences in the field of biomedical statistics and machine learning are required.

Your profile:

  • PhD degree in natural sciences, (bio)informatics, mathematics or related disciplines
  • expertise in deep learning and biomedical statistics
  • good knowledge of written and spoken English
  • ability and motivation to work independently
  • eagerness to develop an own research focus
  • team working skills

We offer:

  • the possibility to work in an interdisciplinary and collaborative environment
  • the opportunity to establish an own research focus (may be also an own research group)
  • flexibility to balance between work and family life
  • an attractive and agile scientific community at the University Medicine campus Dresden
  • an internal prevention program, including courses and fitness in our Carus Vital Health Center
  • a Position according to TV-L conditions (E13; 100%)

Women are explicitly encouraged to apply. Disabled persons with equal qualification will be preferred.

We kindly ask you to apply preferably via our online form to make the selection process faster and more effective. Of course, we also consider your written application without any disadvantages. 

Applicants should submit a full CV, motivation letter, list of publication and a motivation letter including a description of previous research experiences and contact details or recommendation letters of two referees via the online application form with Registration number IMB0920389 until January 31st, 2021. For further information please contact Prof. Dr. Ingo Roeder (