Currently, large amounts of data are collected from diverse sources with complex and non-standard structures. This creates great opportunities for yet better decision making by using the heterogeneous data in various domains such as Industry 4.0 (e.g. smart manufacturing,), healthcare and agri-food. Data fusion is a promising approach for creating added value from this data. We are looking for a Postdoctoral researcher working in this context.
The post-doc is expected to work on the development of methods and techniques integrating those heterogeneous data as well as analyzing data with complex and non-standard structures. The test domain will be smart industry, where data originating from multiple systems and other sources including IoT can be transformed into information using data fusion and data science methods. The explicit scope of the post-doc position will be defined based on the preferences and experience of the selected candidate.
This project is part of a larger research initiative on information and data fusion and intelligent interaction between human and machine for joint decision making. The post-doc researcher will join the newly built team working in this domain. Moreover, this line of research is linked to research at DKE especially in the areas of machine learning and signal processing.
The successful candidate will:
1. Support the R&D activities of the department in data fusion and machine learning.
2. (Co-) author scientific, peer-reviewed papers, submitted to top conferences and journals in the field of data fusion and machine learning.
3. Provide support and/or manage funding acquisition activities and proposal writing (national and international, e.g. Horizon Europe).
4. Support the department in teaching activities.
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