Medical guidelines ensure that clinical practice is maximally effective, but they often lag behind the state-of-the-art. New research is published at an astonishing rate - PubMed grows with 2000 papers per day - while it typically takes at least three years before a single guideline is updated. This project intends to speed up the update cycle of medical guidelines by the automatic collection and interpretation of evidence, as inferred from hospital data, knowledge models and Medical Linked Open Data sets. The project is aiming to combine data driven approaches and knowledge intensive approaches. The project is carried out in close cooperation with medical practitioners.
 
The increasing availability of various types of data provides opportunities for data-centric approaches to the guideline updating problem, as compared to the slow, labor-intensive process that exists today. In particular, it seems promising to exploit event data on the actual execution of medical processes and open data from a variety of sources. The project will focus on:
 
1. The identification of a conflict between the prescribed process model (the guideline) and the observed process model (event data);
2. The observation of unacceptably poor results of the prescribed process/guideline (quality indicators);
3. The occurrence of new knowledge in the scientific literature (open data);

The project will use Linked Open Data to build a bridge from guidelines to mined models, indicators and data, but also to bootstrap process mining. We will investigate different methods for mapping mined process models onto guidelines (KR-based, rule-based or based on graph structure).

To fill the PhD position for this project, we will be looking for an enthusiastic candidate with a strong motivation and the ability to proactively tackle the project’s research questions. The candidate should have a background (master degree or equivalent) in either medical informatics or in computer science/artificial intelligence, and have an outspoken interest in the medical domain. Since the medical guidelines in question are available only in Dutch, proficiency in this language is a very strong advantage for a successful execution of the project. Experience with data modelling (linked data) and data analysis techniques, in particular process mining, is considered as another advantage.
 
Successful candidates are expected to write scientific papers for international peer-reviewed journals, present his/her work in international conferences, and finalize the work in a PhD thesis.
The responsibilities of a PhD also include giving a limited amount of teaching.

The initial appointment will be for a period of 1 year. There is the possibility to extend the initial appointment with 3 years. You may find information about our excellent fringe benefits at http://www.workingatvu.nl.   
• Remuneration of 8.3% end-of-year bonus and 8% holiday allowance;
• Participation in a solid pension scheme (ABP);
• A minimum of 29 holidays in case of full-time employment. 
  
The salary will be in accordance with university regulations for academic personnel, and range from a minimum of € 2222,00 gross per month in the first year up to a maximum of € 2840,00 gross per month (salary scale 85.0-3 CAO NU) based on a full-time employment. 

http://www.vu.nl/en/index.asp

Vrije Universiteit Amsterdam is a leading, innovative, and growing university that is at the heart of society and actively contributes to new developments in teaching and research. Our university has ten faculties which span a wide range of disciplines, as well as several institutes, foundations, research centres, and support services. Its campus is located in the fastest-growing economic region in the Netherlands (the Zuidas district of Amsterdam), and provides work for over 4,500 staff and scientific education for more than 23,000 students.

Research at the Faculty of Sciences focuses on the areas of Life & Health, Networked World, Fundamentals of Science, and Energy & Sustainability. The faculty’s teaching activities are directly linked to this excellent research. Cooperation with other faculties on the Vrije Universiteit Amsterdam campus generates attractive, high-quality Bachelor’s and Master’s programmes.  At international level, the faculty cooperates closely with leading scientific institutes and other partners.
 
The VU Department of Computer Science has approximately 170 members, including 35 tenured staff members and 40-50 PhD students. The tenured staff members form the essential basis for the functioning of the department. A tenured staff member is required to make significant contributions to the research and education programmes, and to spend effort on specific tasks at the department level.