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Research Associate (PhD Candidate) (m/f/d)
Bremen
Aktualität: 03.12.2021

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03.12.2021, JACOBS UNIVERSITY BREMEN
Bremen
Research Associate (PhD Candidate) (m/f/d)
Future 6G communications systems will operate on high frequency bands of 100s of MHz (mmWave/sub-THz) and rely strongly on AI/ML. This new paradigm will enable 6G systems to exploit radio signals beyond transmitted information, to extract also information on its surrounding environment, including the shape, location, and status of objects. This position is sponsored by a Tier-1 automotive and communication systems supplier and is intended to generate advanced scientific results suitable both to patenting and to be published as academic articles, on topics related to the indicated above. Examples of which are: ML-based recognition and identification through the application of mmWave and sub-THz beamforming, waveform design and signal processing for imaging, multi-object and posture identification for V2X applications. Exemplary Tools: Generative Adversarial Networks (GAN), conditional Deep Convolutional Networks (cDCN), hypergraph matching, Generalized Labeled Multi-Bernoulli Filters (GLMBF), and Long Short-Term Memory (LSTM) networks. Dynamic Dilution of Precision for Path Prediction for Tracking in V2X scenarios. Context: prediction of the trajectories of multiple objects in the context of Connected Autonomous Driving using typical mobility features and qualifiers, such as direction of bearing, likelihood of motion, etc., using the latest tools in AI/ML in combination with classical multi-target tracking schemes to build a dynamic probabilistic picture of the scenario captured by the mmWave/sub-THz imaging system. Conduct research on the aforementioned topics, producing both internal documentation towards patents as well as academic articles to be submitted to high-quality journals and conferences. Build simulation tools to demonstrate the efficacy of new methods and algorithms proposed. Integrate results with those of other members of the research team under the same project.
M.Sc. degree in Electrical Engineering, with a focus on Wireless Communications and/or Signal Processing, with a track record of publications in research topics related to the description above. Expertise on both the algorithmic development and the application of AI/ML solutions, especially in the context of signal processing and wireless communications. Strong mathematical background, particularly in optimization theory, with proficiency in Matlab and Python. Daily familiarity with Latex. Familiarity with modern machine learning libraries such as TensorFlow, PyTorch, and JAX. Experience in image analysis and processing is a plus. Demonstrated ability to conduct scientific research and produce high-quality publications. Fluent English and the ability to collaborate with fellow researchers in a team.

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