PhD student in Health Data Science

Descrizione

PhD student in Health Data Science Sintesi in italiano (traduzione automatica): Il Dipartimento di Informatica Medica dell'Erasmus MC offre una posizione di dottorato a tempo pieno focalizzata sulla farmacovigilanza basata su intelligenza artificiale e sanità. Il candidato entrerà a far parte di un team multidisciplinare impegnato in collaborazioni internazionali, incluso il progetto OHDSI, per valorizzare i dati sanitari osservazionali. Il progetto di dottorato si concentra sullo sviluppo di metodi per supportare la farmacovigilanza utilizzando dati reali. Le principali mansioni includono la definizione, implementazione e validazione di flussi di lavoro per la rilevazione di segnali di sicurezza. È richiesta una laurea in un campo pertinente, preferibilmente in Data Science o Informatica, e competenze in analisi dei dati e intelligenza artificiale. The Department of Medical Informatics at Erasmus MC invites applications for a full-time PhD position at the forefront of AI-based pharmacovigilance and healthcare. You will join our innovative, multidisciplinary team engaged in international collaborations, including the Observational Health Data Sciences and Informatics (OHDSI, https://ohdsi-europe.org ) initiative, dedicated to bring out the full value of observational health data through the OMOP Common Data Model and large-scale analytics. This PhD project focuses on methods development to support pharmacovigilance using real-world data (RWD). You will define, implement, benchmark, and validate workflows for reliable detection and validation of safety signals across observational data networks. Key research areas may include: Developing and evaluating AI-solutions in line with responsible AI principles (e.g. robustness, fairness, interpretability) to ensure equitable performance across diverse populations and compliance with regulatory expectations. Advancing methods for personalized risk assessments, with a focus on sex/gender differences and vulnerable subpopulations (e.g. pregnant women, children, elderly) to improve safety monitoring and interventions. Assessing the effectiveness of AI-supported pharmacovigilance when applied across multiple RWD sources. Throughout your research, you will address challenges in large-scale, federated observational studies and contribute to the advancement of signal detection and evaluation methodologies within a leading international research environment. Annuncio in inglese. Fonte: Euraxess (Commissione europea).