MULTIMODAL DATA CAPTURE AND ANALYSIS (W1)
For this position, we seek a committed early-stage researcher with a visible international research profile and a strong research agenda. Your research focuses on the field of multimodal data capture and analysis.
To enable research grounded in these data sources, procedures for capturing and analyzing data diversity must comply with the latest standards and consider state-of-the-art technology and algorithms. Building reliable frameworks to capture, integrate, and analyze data empowers new research designs and AI models, especially if these transcend and integrate multimodal data sources. This process requires ongoing reflection on the ethical dimensions of AI to ensure the development of responsible solutions.
You have expertise in one or ideally more of the following fields: computer vision, pattern recognition, data stream management, multimodal analytics, data mining, interdisciplinary applied AI, and multimodal machine learning.
You show a strong commitment to high-quality research as demonstrated by continuous contributions to leading national and international scientific associations and (premier AI) conferences during the recent years, and an initial track record of publications in conference proceedings or highly ranked international journals according to the CORE ranking (B or higher).
You have initial experience in the acquisition of or participation in externally funded projects. In terms of teaching, we are seeking a candidate with first teaching experience in the field at the bachelor's level, ideally also at the master's level, who offers high-quality, innovative teaching.
Most of our courses at the bachelor's and master’s level are taught in English. Consequently, we expect an excellent command of written and spoken English.