Systematic reviews and meta-analysis, including reviews of individual participant data, are vital to healthcare. They have become the cornerstone of evidence-informed decision making about health for patients, healthcare professionals and health policy organizations such as the World Health Organization. Currently, systematic reviews have become complicated and time-consuming (often taking more than 1 or 2 years of work to complete). Fortunately, some steps of the review process have the potential to benefit from current advances in natural language processing, text mining, and machine learning. For a successful implementation within the systematic review process both development and validation of (semi-) automation tools employing these techniques need to be performed.
As the successful candidate for this position, you will be studying various methodological challenges, using modern machine learning, text mining, and other techniques from the artificial intelligence field, with regard to the (semi-)automation of all steps of the systematic review and meta-analysis process, to enhance the conduct and speed of reviews in the medical domain. Additionally, we will evaluate to what extent machine learning methods can more easily and rapidly evaluate whether medical reports have adhered to existing reporting guidelines. You will participate in a multidisciplinary team, attend weekly meetings, provide presentations of your research both during these meetings and (international) conferences, and contribute to teaching epidemiology to (medicine) students.
In this position, you will work and be supervised in the Department of Epidemiology as part of Cochrane Netherlands and the Methods of Epidemiological Research team, in the Julius Center at the UMC Utrecht. This group evaluates and develops new research methods for both primary and meta-epidemiological research. You will be part of an energetic, enthusiastic team of more than 30 colleagues from different backgrounds. The Julius Center has an extensive national and international network.
Applicants for this position should have a relevant MSc to the position. For example, in epidemiology, biomedical or health sciences, biostatistics, medical informatics, technical medicine, (applied) data sciences, artificial intelligence, or natural language processing. You demonstrate a keen interest in the methodology of medical research, have expertise in working with machine learning techniques, and are capable of working in a team and communicating about your ideas with peers. Fluency in written and spoken English is required, and fluency in Dutch is an advantage.
If you would like to know more about Cochrane Netherlands, take a look at our website (www.cochrane.nl). If you have any questions about this vacancy, please contact Lotty Hooft, Director of Cochrane Netherlands ([email protected]) or Anneke Damen, senior reviewer at Cochrane Netherlands ([email protected]).