The University of Kassel is a modern and growing University with round about 25.000 students. It has an extraordinary wide section with expertise of nature, technique, culture and society.

The following position in the Department of Electrical Engineering / Informatics at the University of Kassel is open for applications:

Postdoc / Scientific Assistant (m/w/d), EG 14 TV-H, fixed-term and full-time position (currently 40 hours per week)

Closes: 29.06.2022
Date of Hire: as soon as possible
Reference: 35107

Please send your application with the usual informative documents, stating the reference number in the subject line, via the online form. We have compiled further information for you in our FAQ.

In exceptional cases, we will also accept your application documents in paper form addressed to: The President of the University of Kassel, 34109 Kassel, Germany, or via mail to bewerbungen[at]uni-kassel.de, stating the reference number.

In the case of postal applications, please submit only copies of your documents (no folders), as these cannot be returned. All documents will be destroyed after completion of the selection process in compliance with data protection regulations.

The full-time position is initially limited until 31.03.2023 within the project “KI-Data Tooling (KI-DT), funded by the BMWI according to the project duration (§ 2 Abs. 2 WissZeitVG). An extension of the employment is planned.

The Department “Intelligent Embedded Systems” (IES) conducts research in the area of foundations and applications of methods of data analysis, machine learning (e.g., deep learning, active learning), and artificial intelligence. In the focus of basic research are, for example, self-learning and self-organizing systems, methods of collaborative and active learning, methods of transfer learning, or techniques for real-time analysis of time series. In the area of applied research, the focus is on energy systems, automotive (autonomous driving) and experimental physics/materials. The IES department currently has about 25 employees working in the above-mentioned areas.

Research within the KI-DT project, particularly in the following areas:

  • Methods for highly automated annotation of data (e.g., camera, LiDAR, and RADAR data) for the training of machine learning methods (especially deep learning approaches).
  • Active learning methods for object detection and for intention detection of vulnerable road users.
  • Modeling methods for quantifying aleatoric and epistemic uncertainty in Deep Learning.
  • Methods for fusing information from several sensors such as LiDAR, RADAR, or cameras for the highly automated annotation of data.


  • PhD in Computer Science completed with very good result, preferable in the above areas.
  • Very good fundamental knowledge in machine learning and data analysis, preferable in the above areas.
  • Successful scientific career with publications in the relevant fields of activity.
  • Experience in obtaining third-party funding (e.g. BMBF, BMWI, DFG).
  • Experience in the application of machine learning methods, especially in the area of deep learning, preferable in the above areas.
  • Experience in programming especially in Python, but also other programming languages.
  • Strong knowledge of AI tools, e.g., PyTorch, Tensorflow, Sklearn, Pandas, OpenCV, and Numpy.
  • A structured working method that allows you to lead in a team.
  • Curiosity for challenges in machine learning applications in the field of automated driving.
  • Independent and goal-oriented work style and enjoyment of scientific work.
  • Good knowledge of German and English, both written and spoken (at least comparable to B2)

Of advantage are:

  • Experience in active learning for object detection in images and experience in time series analysis, especially intention detection and activity recognition.
  • Experience in product management.

Our offer:
As an employee of the department of Intelligent Embedded Systems you will

As an employee of the University of Kassel

In addition, you will benefit from the advantages of employment in the public service such as:

For further information please contact Prof. Dr. Bernhard Sick, tel.: +49 561 804-6020, E-mail: bsick(at)uni-kassel.de.

You can find more jobs at stellen.uni-kassel.de

The protection of your personal information is very important to us, so we will handle your personal information with care. By your application, you allow us the storage and use in the sense of the Hessian Data Protection and Freedom of Information Act. You can object to this at any time. Your personal data will be deleted.

Information according to Art. 13 DSGVO for the application process at the University of Kassel can be found at:

The University of Kassel is very interested in the professional satisfaction of its employees. It is distinguished as a family-friendly university and, in the interests of equal opportunities, strives to offer everyone the same opportunities for development and to counteract existing disadvantages. It promotes the Family Welcome Service and also the Dual Career Service for positions that are scientifically and academically filled. One of the strategic goals of the University of Kassel is to significantly increase the proportion of women in research and teaching. Applications from women are therefore particularly welcome. Seriously handicapped and equivalent applicants are given preference if they have the same suitability, qualifications and professional performance. Full-time positions are generally divisible (except when filling civil servant positions). Applications indicating the Position Number, which may be in digital form, should be sent to the President of the University of Kassel, 34109 Kassel, Germany or bewerbungen@uni-kassel.de, quoting the applicable reference number.
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