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You will focus on data science aspects of the realization of a linked data set in which data from healthcare providers, health insurers, municipalities and demographic data are used to improve early detection, to compile risk profiles and to be able to develop and implement innovative healthcare concepts. Optimization of possibilities to reuse routine data from healthcare and other sources, with datamining, text mining and advanced recoding techniques, will be one of the innovation areas. Data about living environment and real-life world data as collected by citizens / patients will also be involved. The linked dataset will act as the basis for the PH Living Lab. Data analytics and data visualizations can be deployed on an individual and aggregated level. Your work consists of deploying and monitoring behavioral interventions on an individual and group level and improving management and organization of care organizations by giving empirical knowledge a role in the policy cycle (planning, funding). The methodological development of how such observational datasets can be used to demonstrate effects of deployed interventions on outcomes and results, provides the methodology for a learning health system. To be able to do this successfully, the various data science process steps must be carefully designed and tested in close coordination and cooperation with biomedical (epidemiology, biostatistics), but also other relevant disciplines such as Governance and Population Health Economics. This leads to a number of research lines that will be set up jointly with LIACS and LUMC colleagues from LUMC Campus The Hague and from which social impact will be generated in education and implementation programs. You will combine the fields of data science (computer science/statistics) with health science. The chair will use knowledge from both fields, and will contribute to both fields.
· You are an experienced researcher with demonstrable teaching abilities
· You will focus on conducting research and initiating new projects for which you know how to get funding
· Your main focus is to conduct research on how datascience assets and applications can effectively support people to gain health and remain as healthy as possible
· To this end you will work in an interdisciplinary setting in both the LUMC (2/3 Campus The Hague) and LIACS (1/3)
· Your data sets consist of information from several parties in healthcare and patients/people themselves
With the persistent increase in the number of chronic somatic disorders worldwide and the increasing health gap between populations in higher and lower social economic circumstances, or between developed and lesser developed areas, the question of how people can effectively gain health and remain as healthy as possible has enormous societal relevance. In this context, to be able to generate as much evidence as possible, population health sciences and population health management increasingly often rely on advanced analysis of FAIR organized, however scarcely coded, routine data from healthcare and adjacent domains (including patient generated data), instead of, or solidly linked with, structured research data from dedicated cohorts and populations. Advanced risk stratification among populations, based on analyses of routine and linked datasets, will support structured and indicated interventions that promote health at an individual and societal level. The current project provides for more solid evidence on risk stratification and prediction in (sub-) populations. However, it also provides for more advanced use of data for continuous evaluation, implementation and monitoring of interventions with the Population Health Living Lab the Hague as the infrastructural basis.
We are looking for a professor with excellent research qualities in the field of advanced analysis of large scale heterogeneous data sets (structured and unstructured). You have an internationally renowned reputation in the field of data science and proven affinity with interdisciplinary research. You also have proven affinity with the health domain and the ability to attract prestigious national and international personal grants, as well as the ability to initiate international research programs and consortia. Furthermore, you have experience in establishing research programs and supervising and coordinating scientific research. You are able to supervise and inspire undergraduate, graduate, and PhD students and researchers. To this end, you possess excellent communication and social skills. In addition, you have significant teaching experience at the undergraduate and graduate level and the willingness to contribute to LUMC and LIACS’ educational activities in the bachelor and master, primarily in the LUMC Campus The Hague master program Population Health Management and the LIACS bachelor and/or master program.
Your salary will be based on your education and experience and is based on scale 16 of the collective labor agreement of the university medical centers.
At the Leiden University Medical Center, we continuously work on improving patient care. We invest in groundbreaking, international research and work with the latest equipment. Together with our team of doctors, medical specialists, teachers, academic researchers and supporting staff, we aim for the best quality in health care, education and international research. And we need you to realize our goals!
Your primary affiliation will be the LUMC, located in LUMC Campus The Hague. Your secondary affiliation will be LIACS, located in the Bio Science Park in Leiden. 2/3 of the integrated activities will be embedded, paid for and carried out at the LUMC The Hague, and 1/3 of the integrated activities will be embedded, paid for and carried out at LIACS in Leiden. At the LUMC Campus The Hague, you will contribute to the Population Health Living Lab The Hague, and substantially to the population health dataset in which multidisciplinary research across different faculties, with data science as one of the core disciplines, is conducted. At the computer science institute LIACS, you will be part of, and contribute substantially to, the artificial intelligence and data science focus area. You will collaborate with existing groups focusing on automatic machine learning (Prof. Hoos), natural and evolutionary computation (Prof. Bäck), reinforcement learning (Prof. Plaat), and data science (Prof. Kraaij).
Leiden University Medical Center (LUMC)
Albinusdreef 2, 2333 ZA, LEIDEN
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