Deadline: 31 Dec 2017
PhD TACTICS (Techniques for the Analysis of Client-Team InteraCtionS) (V32.3080)
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:
- A solid background in Computer Science, Data Science, Mathematics, or any other quantitative degree (demonstrated by a relevant Master);
- Ideal candidates have a strong background in process/data mining, machine learning, predictive analytics or data science in general;
- Candidates from non-Dutch or non-English speaking countries should be prepared to prove their English language skills by providing IELTS- or TOEFL-scores;
- Good communicative skills in English, both in speaking and in writing;
- Good communicative skills in Dutch, both speaking and in writing, are preferred given the project context;
- Candidates are expected to realize research ideas in terms of prototype software, so software development skills are needed.
Note that we are looking for candidates that really want to make a difference and like to work on things that have a high practical relevance while having the ambition to compete at an international scientific level (i.e., present at top conferences and in top journals).
Conditions of employment
- full-time employment as a PhD-candidate for a period of 4 years,
- annually 8% holiday allowance and 8.3% end of year allowance;
- support with your personal development and career planning including courses, summer schools, conference visits etc.;
- a broad package of fringe benefits (including an excellent technical infrastructure, child care, moving expenses, savings schemes, coverage of costs of publishing the dissertation and excellent sports facilities)
Information and application
The application should consist of the following parts:
- Cover letter explaining your motivation and qualifications for the position;
- Detailed Curriculum Vitae, including list of publications;
- Key publications (or links to download).
- Description of software developed (or links to GitHub) if any.
- A copy or a link to your Master thesis. If you have not completed it yet, please explain your current situation.
- A transcript of your grades.
- For more information about this position contact dr.ir. Joos Buijs (Assistant Professor), e-mail: email@example.com.
- For information about employment conditions please contact P. Hertogs LLM, MSc (HR advisor), e-mail: firstname.lastname@example.org.
Acquisition further to this vacancy is not appreciated.