Job description
Global infectious disease data are relevant for early decision making to control and contain outbreaks. Data infrastructure remains limited. Global.health is a data science initiative addressing a core need in global disease surveillance integrating data across countries and surveillance systems in the first 100 days of new outbreaks. This includes partnerships with other initiatives such as the WHO and the ISARIC clinical research platform. Data quality remains a core issue and needs to be addressed more systematically. The postholder is expected to:
- Oversee the whole chain of collection, transformation, documentation, and dissemination of ISARIC data
- Ensuring ISARIC and G.h data quality and timeliness
- Develop metrics for evaluation and assessment of data quality and timeliness – publishing of guidelines for data science community
- Develop visualisations and analysis code for data quality assessment
- Recruit external data evaluation board
- Run external data evaluation meetings
- Coordinate and oversee data extraction team (including engineers working on parsers)
- Communicate with external data teams in the wider global health landscape (WHO, JHU, OWID)
- Document data extraction process and publish it according to FAIR principles
- Develop resources for users of data (e.g., handbooks)
- Engage with project participants (ISARIC partner sites)
- Oversee human-in-the-loop data quality platform (implemented by UX designer and front end engineer)
Where Covid-19 has resulted in substantial disruption to your work or research outputs, please explain this by providing an additional paragraph in your supporting statement.
The University of Oxford is committed to equality and valuing diversity. All applicants will be judged on merit, according to the selection criteria.
This post is full time and available immediately.
The closing date for applications is 12.00 noon on Wednesday 17th May 2023 interviews are likely to be scheduled for late May.