For this project we are looking for an ambitious candidate who has a MSc in a relevant discipline (biomedical sciences, data science, (pharmaco)epidemiology or similar) and is interested in European monitoring of myocarditis cases in COVID -19 vaccination with observational research, common data model, machine learning and using data from daily clinical practice and existing European registries.

Our healthcare system has entered a new era as a result of the digitalisation of healthcare information, in which ever-increasing amounts of clinical and registry data are collected, stored, mapped, linked and analysed electronically. This data is also called real-world data to indicate that it is clinical data rather than data collected in an experimental/controlled setting. In the past decade, the re-use of this data for research purposes has increased rapidly. Real-world data have therefore also become an integral part of vaccine monitoring research and are essential for studying the risks and benefits of COVID -19 vaccines in to provide insights in their effectives and safety patterns..

An essential component for real-world evidence is data quality, which must be sufficient to support decision-making in daily practice. A causal framework when designing studies with data from daily practice is therefore of great importance. Testing causal relationships in observational data can be used to study the association between medication and clinical outcomes in a wide range of patients in daily practice.

The goal of this study is to characterize the natural history, clinical course, outcomes and risk factors for myocarditis temporally associated with COVID-19 vaccination.

Although most cases of vaccine-associated myocarditis have been described as mild and self-limiting, additional data are needed to characterize the natural history and long-term outcomes of these events and characterize risk factors for both occurrence and severity.

For this project we are looking for an ambitious PhD-candidate with a MSc in a relevant discipline (medicine, biomedical sciences, data science, (pharmaco)epidemiology or similar). You have an interest in European cohort monitoring of COVID -19 vaccine in observational research, common data model, machine learning and using data from daily clinical practice and existing European registries.. Candidates with experience in the field of Epidemiology and programming skills in R software are preferred. The candidate can work independently and is interested in collaborating with different partners and stakeholders in the Europe and the Netherlands. The candidate has good communication skills and has a good command in writing and speaking of the English language. A PhD educational program in clinical epidemiology is part of the offering.

You will be given a temporary appointment for 1 year, which will be extended to 3 years after a positive evaluation of the first year. The gross monthly salary is € 2.495 in the first year, rising to a maximum of € 3.196 (OIO scale). In addition, we offer an annual benefit of 8.3%, holiday allowance, travel expenses and career opportunities. The terms of employment are in accordance with the Collective Labour Agreement for University Medical Centres (UMC).

The maximum salary for this position (36 - 36 hours) is € 3.271,00 gross per month based on full-time employment.

In addition, we offer an annual benefit of 8.3%, holiday allowance, travel expenses and career opportunities. The terms of employment are in accordance with the Cao University Medical Centers (UMC).

The Julius Center

The Julius Center is part of the University Medical Center Utrecht and the candidate works within the ”Global Health” group. The Julius Center is a leading and multidisciplinary knowledge centre for Health Sciences and Primary Care. There is (epidemiological) research in the field of cardiovascular diseases, cancer, infectious diseases, public health, exposome, methods, big data and biostatistics. We also provide education for (bio) medical students, researchers, clinicians, and other healthcare professionals and deliver academic primary healthcare to patients.

The current project involves a close collaboration with VAC4EU (https://vac4eu.org). VAC4EU (Vaccine monitoring Collaboration for Europe) is the sustainability solution of the ADVANCE project which was funded by the Innovative Medicines Initiative from October 2013- March 2019. VAC4EU implements the ADVANCE vision, system and blueprint and enables robust and timely evidence-generation on the effects of vaccines in a collaborative manner in Europe for use by citizens, health care professionals, public health organisations and regulatory agencies. VAC4EU is a multi-stakeholder international association with a study network to run studies and an open community for scientific debate.