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Collaborative Research Center SFB 876 - Providing Information by Resource-Constrained Data Analysis

The collaborative research center SFB876 brings together data mining and embedded systems. On the one hand, embedded systems can be further improved using machine learning. On the other hand, data mining algorithms can be realized in hardware, e.g. FPGAs, or run on GPGPUs. The restrictions of ubiquitous systems in computing power, memory, and energy demand new algorithms for known learning tasks. These resource bounded learning algorithms may also be applied on extremely large data bases on servers.

Assistant Professor (W1) in Smart City Science

With more than 6,200 employees in research, teaching and administration and its unique profile, TU Dortmund University shapes prospects for the future: The cooperation between engineering and natural sciences as well as social and cultural studies promotes both technological innovations and progress in knowledge and methodology. And it is not only the more than 34,600 students who benefit from that. The Faculty for Computer Science at TU Dortmund University, Germany, is looking for a Assistant Professor(W1) in Smart City Science specialize in research and teaching in the field of Smart City Science with methodological focus in computer science (e.g. machine learning and/or algorithm design) and applications in the area of Smart Cities (e.g. traffic prediction, intelligent routing, entertainment, e-government or privacy).

Applicants profile:

  • An outstanding dissertation and excellent internationally recognized publications in the field of computer science methods for Smart Cities
  • Experience in raising third-party funding
  • The willingness to participate in research collaborations within and outside TU Dortmund University, such as CRC 876 "Availability of information through analysis under resource constraints"
  • Language competence in German or English are required
  • Appropiate participation in teaching in the faculty's courses of study

The TU Dortmund University aims at increasing the percentage of women in academic positions in the Department of Computer Science and strongly encourages women to apply. Disabled candidates with equal qualifications will be given preference.

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  Peter Marwedel gives the opening talk at the 21. SASIMI workshop in Matsue, Japan

Peter Marwedel gives the opening talk "Cyber-Physical Systems: Opportunities, Challenges, and (Some) Solutions" at the 21. workshop on Synthesis And System Integration of Mixed Information technologies (SASIMI) in Matsue, Japan. He presents opportunities and challenges of the design of cyber-physical systems. He will additionally attend the panel "What is the next place to go, in the era of IoT and AI?".

Two Best Paper Awards for Subproject B2

Biosignals 2018


Two independent publications from subproject B2 have been honored with a Best Paper Award at different conferences dealing with the automatic classification of nano-objects (e. g. viruses) in noisy sensor data. They provide a valuable contribution to the automatic analysis of medical probes using the PAMONO sensor.

The joint work "Real-Time Low SNR Signal Processing for Nanoparticle Analysis with Deep Neural Networks" of Jan Eric Lenssen, Anas Toma, Albert Seebold, Victoria Shpacovitch, Pascal Libuschewski, Frank Weichert, Jian-Jia Chen and Roland Hergenröder received the Best Paper Award of the BIOSIGNALS 2018.

The joint work "Unsupervised Data Analysis for Virus Detection with a Surface Plasmon Resonance Sensor" of Dominic Siedhoff, Martin Strauch, Victoria Shpacovitch and Dorit Merhof received the Best Paper Award of the IEEE International Conference on Image Processing Theory, Tools and Applications (IPTA) 2017. The approach was developed in cooperation with the Department of Image Processing, RWTH Aachen University.

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