Projeto PRR

Sumário

The prospective employee is expected to work as an Assistant Professor in the field of Health Data Science. 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 big data analytics, machine learning applications in healthcare, predictive modelling, and bridging data science with producing and assessing evidence in health. 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 medical background and knowledge and experience in statistical programming languages (such as R) and data analysis, including supervised learning methods (e.g., regression and classification methods), unsupervised learning methods (e.g., k-means) and predictive modeling. Knowledge of artificial intelligence-based natural language processing methods and tasks (such as text generation, named entity recognition and question answering, using transformers and/or large language models) will also be required. Knowledge of research methodology and evidence for decision-making is highly appreciated.MEDCIDS has a relevant research and teaching track record in the Health Data Science field. This is indicated by (i) the high number of studies published by its members involving the intelligent analysis of real-world data, (ii) the participation of some of its members in funded scientific projects in Health Data Science, (iii) the involvement of some of its members in bridging data science and evidence-based decision-making (e.g., participation in the artificial intelligence group of the GRADE working group), (iv) and by the participation in technology transfer and services provision activities (involving public, private, national or international entities – e.g., participation in data analysis activities involving international mobile health databases). This research activity is done in close connection with the Associate Laboratory RISE (Health Research Network). In fact, Thematic Line 4 of RISE has, among its main scientific fields, those of big data, artificial intelligence, patient-centred technologies, medical informatics and digital transformation (in connection with medical decision-making).MEDCIDS has also displayed a vibrant teaching activity in the Health Data Science field, with contents on intelligent data analysis, machine learning, and artificial intelligence being some of the cornerstones of the Doctoral Programme in Health Data Science. In addition, some of these contents are taught in the Doctoral Programme in Clinical and Health Services Research (all these programmes are hosted at MEDCIDS). Topics on Health Data Science 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 Science area is necessary.