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Paid Internship
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21Open Positions

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Research Assistant

Technische Universität Berlin
Found 2 weeks ago
Location
Berlin, Germany
Time
Full-time
Work Mode
Not disclosed
Salary
Salary grade 13 TV-L Berliner Hochschulen
Visa Help
Not disclosed
Last Verified
2 weeks ago

Education

  • Master

Skills & Qualifications

Technical Skills

  • Electrical/Computer Engineering
  • Computer Science
  • Mathematics/ Applied Mathematics
  • Physics
  • artificial intelligence / deep learning methods, software, and techniques
  • design of deep neural network structures and training strategies for signal-processing related tasks
  • 6G wireless technology
  • Physical Layer Waveform Design
  • Multi-Dimensional Signal Processing
  • Advanced Multiple Antenna Technologies
  • Electromagnetic Signal Processing
  • reconfigurable electromagnetic metasurfaces
  • Near‑Field Channel Estimation, Positioning, Sensing
  • Distributed and Cell-free Integrated Sensing, RF-Imaging, and Communications

Soft Skills

  • enriching interdisciplinary environment
  • significant potential for broad impact
  • independent research
  • willingness to acquire the respective missing language skills

Job Description

The selected candidates will have opportunities to work in an enriching interdisciplinary environment, with significant potential for broad impact in terms of technology development, industry involvement. The position is funded by the European Project MULTIPLY-6G, focusing on advanced waveform and protocol design for 6G wireless networks. Developing of independent research under the supervision of Prof. Caire in the framework of the EU-funded project MULTIPLY-6G. The focus on 6G wireless technology. The specific topics of research include: 1) Physical Layer Waveform Design for Communications and Sensing based on Multi-Dimensional Signal Processing (antennas, delay-Doppler / time-frequency domains); 2) Advanced Multiple Antenna Technologies Based on Electromagnetic Signal Processing, including reconfigurable electromagnetic metasurfaces; 3) Near‑Field Channel Estimation, Positioning, Sensing; 4) Distributed and Cell-free Integrated Sensing, RF-Imaging, and Communications.

Requirements

  • Successfully completed scientific university degree (Master, Diplom or equivalent) in a field of Electrical/Computer Engineering, Computer Science, Mathematics/ Applied Mathematics, Physics
  • A specific experience with artificial intelligence / deep learning methods, software, and techniques, is particularly appreciated, especially know-how and experience in design of deep neural network structures and training strategies for signal-processing related tasks.
  • Good knowledge of German and/or English required; willingness to acquire the respective missing language skills.

Related Field

  • Software Engineering

Related Subfield

  • AI/ML/GenAI Engineering

Languages

  • German
  • English

Nice to Haves

  • experience with artificial intelligence / deep learning methods, software, and techniques
  • know-how and experience in design of deep neural network structures and training strategies for signal-processing related tasks
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