electrical engineering
[Open soon]
Work description
• Development of more efficient fingerprinting methodologies, including interpolation and data augmentation techniques, adaptive selection of reference points, and reduction of experimental data collection effort. • Implementation and evaluation of new machine learning-based localization models, exploring different WiFi channel characteristics, namely RSSI and, potentially, CSI. • Integration of the developed methods into the RTLS for real-time operation, including experimental validation, comparative performance analysis, and contributions to scientific publications.
Academic Qualifications
• Bachelor's degree in Electrical and Computer Engineering, with a specialization in networking.
Minimum profile required
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Preference factors
• Experience in developing and evaluating indoor localization algorithms, particularly fingerprinting techniques, using Python or C/C++; • Knowledge of data processing, machine learning, and experimental data analysis; • Experience in software development for the acquisition and processing of WiFi network data, namely RSSI and CSI; • Research experience, preferably of at least 1 year, in communication networks or wireless localization systems.
Application Period
Since 22 Oct 2026 to 05 Nov 2026
[Open soon]
Centre
Telecommunications and Multimedia