Ongeveer 17 uur geleden - Radboud Universiteit Nijmegen (RUN) - Nijmegen
The FINDER programme, a research collaboration between Radboud University and Atos, an international leading information technology services company, sets out …
In the context of the newly funded TACTICS (Techniques for the Analysis of Client-Team InteraCtionS) research project, we are looking for a PhD candidate with a strong background in process mining and/or data mining ...
Lunet zorg is a healthcare provider to clients with intellectual and/or physical disabilities in the Eindhoven area. Lunet zorg aims at continuously improving the quality of life of its clients, as well as the effectiveness of their teams. Currently, there is a realization in the organization that the data recorded can, and should, be used to steer this continuous improvement process. Lunet zorg envisions that the data can be used to support the teams in the field by incorporating structural data collection and analysis in the daily way of working. This allows teams to have access to relevant and understandable information, such that they can make the correct decisions for the team and the continuous improvement of the care for the clients. Within the TACTICS research project Eindhoven University of Technology and the Vrije Universiteit Amsterdam (VU) collaborate with Lunet zorg to realize this goal.
The TACTICS project aims at the development of automated techniques to generate insights into the evolving statuses of such clients as well as the way how actions of care teams influence clients. The inputs for these algorithms are large sets of heterogeneous, operational data, such as team reports, sensor data, client records and emergency reports.
The TACTICS project aims to address various data handling and data analytics challenges. First of all, it will be necessary to align sets of heterogeneous and partially unstructured data. Secondly, the concept of a client status, which is non-protocolled, must be developed from this data. Thirdly, it must become feasible to automatically detect the characteristics and variations in team practices. Finally, the team practices need to be related to how client statuses develop over time, such that care organisations can transfer beneficial work practices from one team to the other.
The main focus of this PhD position in on the second aspect: developing approaches to derive the client status from the available data.
The PhD student is expected to combine techniques form the fields of process mining, data analytics, information alignment, and business process improvement. A close collaboration with Lunet zorg, a Dutch care organization, will allow the whole team to use operational data and incorporate essential socio-medical expertise in their work. The PhD candidate will work together with a PhD appointed at the VU, a postdoc to be appointed at the VU, and a postdoc to be appointed at TU/e.
We are looking for candidates that meet the following requirements: