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Digitalization of society provides a treasure trove of data, based on an abundance of sensors and connectivity of services and people. Web and social media offer endless possibilities for people to connect, develop and use digital services. Our increasing data science abilities for data analysis and machine learning drive novel smart services. They provide solutions benefitting society in a large variety of domains, including health, engineering, safety and security, business, and science. At the same time, this digitalization comes with challenges. You can think of concepts like fairness, data quality, and trust, and threats such as fake news that must be addressed. This requires a fundamental inter-disciplinary approach bridging fields like computational statistics, machine learning, image and signal processing, information retrieval, and data processing and management.
The mission of the Data management and Biometrics group (DMB) is to work on explainable data science by developing methods for autonomous, reliable and robust gathering, preparation, and analysis of the data, to enable relevant, trustworthy and explainable results.
To expand and strengthen our areas of expertise we are looking for a colleague at the level of assistant or associate professor specifically with a ‘data engineering’ profile, i.e., someone with a research focus and expertise on one or more of the following topics: natural language processing, information extraction, data cleaning, big data processing, sensor data processing, machine learning (in application to data engineering and/or issues like fairness, explain ability, robustness).
Scientific excellence is a must and should be demonstrated by high-quality output. A successful candidate will also demonstrate her or his intrinsic motivation and strong abilities for teaching at the bachelor and master level. We value a vision on academic teaching, blending the physical and digital experience. The candidate should have excellent communication skills, allowing efficient interaction with colleagues.
The faculty of Electrical Engineering, Mathematics and Computer Science (EEMCS) comprises three disciplines that shape Information and Communication Technology. ICT is more than communication. In almost every product we use mathematics, electronics and computer technology and ICT now contributes to all of societies' activities. The faculty works together intensively with industrial partners and researchers in the Netherlands and abroad and conducts extensive research for external commissioning parties and funders. The research which enjoys a high profile both at home and internationally, has been accommodated in the multidisciplinary research institutes: Mesa+ Institute, TechMed Centra and Digital Society Institute.
University of Twente (UT)
Drienerlolaan 5, 7522 NB, Enschede
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