Research Assistant (EG 13 TV-H) - at the Department of Digital Technology

Half of the position is part of the project "Pilot project for the implementation of a Bachelor of Science plus MINT with orientation phase" funded by the state of Hesse from the study structure program, the other half is part of a LOEWE project at the Department of Digital Technology.

The orientation course is designed as a two-semester orientation phase, which precedes the subsequent six or seven-semester subject-related course. This is an optional focus within the framework of the model degree course. The aims of the innovative model are to expand the target group of potential STEM students, to facilitate the study entry phase by compensating for different learning requirements, to prevent students from dropping out and changing subjects, to acquire key skills relevant to successful study at an early stage and to increase the proportion of women in STEM subjects.

Tasks in the plus MINT pilot project:

• Participation in the implementation of the model degree program as of 01.10.2019 in cooperation with the other project participants,
• Development of a specific advisory concept including the development of a range of information and assessment options to check individual preferences in coordination with the other central and decentralized offers; testing of the advisory concept in the jointly developed structure of the model degree course,
• Conception and organization of new courses (lecture series, orientation preliminary courses, tutorials, workshops, practical projects, work placements), guidance of tutorials and practical projects as part of the orientation course,
• Coordination and adaptation of sample timetables; dovetailing with the orientation phase of the subsequent subject-specific study components,
• Participation in the development of a joint regional and nationally effective student marketing strategy including operational implementation for the model degree program for the first two study cohorts
• Participation in the evaluation of the pilot project during the funding period until 31.12.2020
• Participation in project documentation and project reporting.

As part of the LOEWE research cooperation with an industrial partner, algorithms for digital image processing and methods from machine learning (artificial neural networks) are to be developed and implemented with hard real-time requirements on CPU/FPGA systems.

Tasks within the LOEWE project:

• Processing of a research project in the field of digital image processing and machine learning,
• Development of concrete algorithms from classical image processing as well as design and training of artificial neural networks,
• Implementation of the results on system-on-chips consisting of CPUs and field-programmable devices (FPGAs),
• Supervision of corresponding, project-sponsored student projects,
• The pursuit of an additional scientific qualification (e.g. doctorate) is expected.

Requirements:

• An excellent university degree in electrical engineering, computer science or a comparable degree program.
• Very good programming skills in a relevant programming language (e.g. Python or C/C++) and programming experience,
• Knowledge or experience in at least two of the areas of digital image processing, machine learning with neural networks, design of hardware circuits with VHDL or Verilog,
• System integration/integration in an industrial environment (PLC control).

Advantageous are:

• Thorough and independent working methods combined with a high ability to work in a team
• A high degree of organizational skills
• Interest and experience in supporting and advising first-year students

If you have any questions, please contact Prof. Dr.-Ing. Peter Zipf, Tel.: 0561-804-6379, E-Mail: zipf[at]uni-kassel[dot]de.

The protection of your personal data is important to us, which is why we will handle your personal data with care. If you provide us with your data, you authorize us to store and use it in accordance with the Hessian Data Protection and Freedom of Information Act. You can object to this at any time. Your personal data will then be deleted.

In the interests of equal opportunities, the University of Kassel endeavors to offer women and men the same development opportunities and to counteract existing disadvantages. The aim is to significantly increase the proportion of women in research and teaching. Qualified women are therefore expressly encouraged to apply. Severely disabled applicants with equal aptitude and qualifications are given preference. Full-time positions are generally divisible. Please only send us copies of your application documents (no folders), as these cannot be returned after the selection process has been completed; they will be destroyed in accordance with data protection regulations. Applications with informative documents should be sent to the President of the University of Kassel, 34109 Kassel or bewerbungen[at]uni-kassel[dot]de, quoting the reference number, also in electronic form.