Projeto PRR

Sumário

The prospective employee is expected to work as an Assistant Professor in the field of Health Data Sciences; 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 research studies that involve applying advanced statistical and data mining techniques to analyze large datasets and extract meaningful insights. 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 clinical background and knowledge and experience in advanced data analysis (including using machine learning methods).MEDCIDS has a relevant research and teaching track record in the Health Data Sciences field. This is indicated by (i) the high number of machine learning algorithms developed and data mining techniques applied to a number of healthcare data and applications of artificial intelligence in healthcare, finance, and other domains, that were published by its members, (ii) by the participation of some of its members in funded scientific projects in Health Data Sciences field, (iii) by the involvement of some of its members with academic institutions, facilitating knowledge exchange and interdisciplinary research initiatives, (iv) and by the participation in technology transfer and services provision activities (involving public, private, national or international entities – e.g., participation in international conferences and workshops, contributing to the dissemination of knowledge and fostering collaboration within the research community). 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 Health Data Sciences field, with contents on statistical modeling studies applied to healthcare, data visualization, predictive analytics, and machine learning methodologies, being one of the cornerstones of the Doctoral Programme in Health Data Sciences and of the Master’s Degree in Medical Informatics. In addition, these contents are taught in the Clinical and Health Services Research Doctoral Programme (all these programmes are hosted at MEDCIDS). Topics on Health Data Sciences 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 Professor in the Health Data Sciences area is necessary.