The positions lie in the intersection of information theory, communication theory, and machine learning with a particular focus on security and privacy听of information systems and machine learning for communications. The job is associated with the goal of graduating with a Dr.-Ing. (German听equivalent of a PhD) degree.
Qualifications and personal qualities:
- Applicants must hold a Master degree or equivalent in electrical engineering, computer science, information technology, mathematics, or听similar/equivalent fields, or must have submitted his/her Master thesis for assessment prior to the application deadline. It is a condition of听employment that the Master degree is awarded.
- The applicants should have excellent mathematical knowledge of probability theory and linear algebra.
- Solid understanding of information theory and/or communication theory is a requirement. Further knowledge in machine learning and/or signal听processing is a plus.
- Applicants must be able to work independently and in a structured manner, and demonstrate good collaborative skills.
- Fluency in spoken and written English.
- Experience in one or more of the following programming languages/environments: Python, MATLAB, C/C++, TensorFlow.
We offer:
- An excellent and professionally challenging working environment.
- Full-time temporary employment with a competitive salary at pay grade TVL-E13.
- No tuition fees for PhD studies.
Your application must include:
- A brief summary of your research interests and motivation
- CV
- Transcripts and diplomas showing completion of the bachelor's and master's degrees, or official confirmation that the master's thesis has been听submitted
- Relevant certificates and references
- Publications in your name
How to apply?
Applications must be submitted via the official job portal of the University of Siegen. For further information about the opening please see also the official postings听听听听补苍诲听听听 which provide a link to the official submission system.听
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For further information about the positions and the application procedure please contact Rafael Schaefer via听[email protected]