Projeto PRR

Sumário

The prospective employee is expected to work as an Assistant Researcher in the field of Biostatistics. The employee is expected to work in research and teaching activities at the Department of Community Medicine, Information and Health Decision Sciences (MEDCIDS) of the Faculty of Medicine of the University of Porto. In particular, the employee is expected to work on data quality assessment, health care quality indicators, development of predictive models (machine learning and statistical analytical techniques), risk-adjustment models for causal inference/health technology assessment, and generation of evidence based on real-world data. The employee is expected to have knowledge and experience in doing research and teaching in these fields. In addition, the employee is expected to have a mathematics background and knowledge and experience in data analysis within clinical and health services research (including exploratory data analysis methods and modelling using statistical and machine learning techniques).MEDCIDS has a relevant research and teaching track record in the Health Data Science/Biostatistics field. This is indicated by (i) the high number of publications in which its members participate in the data analysis or in the planning, implementation and or results’ interpretation phases of studies, (ii) the participation of some of its members in funded scientific projects with important contributions in leveraging health data to improve the clinical decisions process and support health policies (e.g. HfPT and NanoStima, 1st.IndiCare, CUTEheart), (iii) and by the participation in technology transfer and services provision activities (involving public, private, national or international entities). This research activity is done in close connection with the Associate Laboratory RISE (Health Research Network). In fact, Thematic Line 4 of RISE is fully dedicated to health policy and digital transformation, having as its scope “development and assessment of methods and technologies to improve biomedical sciences and healthcare”.MEDCIDS has also displayed a vibrant teaching activity in the Biostatistics field, with contents on Biostatistics, Machine Learning, Survival analysis and Causal Inference being some of the cornerstones of the Health Data Sciences Doctoral Programme and of the Doctoral Programme in Clinical and Health Services Research (all these programmes are hosted at MEDCIDS). Topics on Health Data Science/Biostatistics will also be of key importance to the BSc course in Digital Health in Biomedical Innovation, in particular to its branch of Data Analysis and Artificial Intelligence in Health. Of note, several of the partners of this BSc course correspond to public or private entities with whom MEDCIDS has collaborated in technology transfer or service provision activities. Given this background and the need to further develop research and teaching activities in this field, hiring an Assistant Researcher in the Biostatistics area is necessary.