Associate Professor in GNSS Remote Sensing and Artificial Intelligence

This role of Associate Professor in GNSS Remote Sensing and Artificial Intelligence requires advanced expertise in Global Navigation Satellite Systems (GNSS) technology and its applications in remote sensing. The candidate should have a strong foundation in satellite-based positioning, navigation, and timing, along with proficiency in remote sensing techniques that utilize GNSS data. Expertise in artificial intelligence (AI) is essential, including knowledge of machine learning algorithms, data analytics, and their integration with GNSS data to improve sensing accuracy and interpretation. The position demands experience in research and development, likely including designing and implementing AI models for processing and analyzing large-scale geospatial datasets derived from GNSS sensors. A solid academic background is expected, typically at the doctoral level or equivalent, with a focus on geospatial sciences, electrical engineering, computer science, or related fields. The candidate should demonstrate the ability to teach, mentor, and publish in these interdisciplinary domains. Familiarity with programming languages commonly used in AI and remote sensing, such as Python, MATLAB, or R, and experience with AI frameworks like TensorFlow or PyTorch, would be highly relevant. Additionally, knowledge of satellite communication protocols, signal processing, and data fusion techniques will be advantageous. The role likely involves collaboration with academic and industry partners, requiring strong communication skills and the ability to lead research projects. Overall, the position demands a blend of deep technical knowledge in GNSS and AI, research excellence, and academic leadership capabilities.