About the role

The Research Fellow will build and validate a machine learning model for Indonesia that can produce predictions for health costs for various disasters including earthquakes, tsunamis and floods. The relevant data will be extracted from longitudinal household surveys for Indonesia. The post holder will work closely with Dr. Rozana Himaz and Dr. Saman Ghaffarian, who will provide guidance and support as required. The work will include contributing to an associated journal article and organising a webinar. The research will form a part of the key work for the UK-ISPF funded project ‘Social Finance for Better Post-Disaster Health (SoFIT)’, a two-year collaboration between UCL RDR and the Resilience Development Initiative in Indonesia, -. The aim of the project is to understand patterns in post-disaster health and recovery at the household-level to inform the development of novel financial instruments that can support disaster risk reduction.

About you

The post-holder should be a PhD student or post-doc with excellent analytical and quantitative skills. Prior experience with developing machine learning models, analysing household survey data and a keen interest in interdisciplinary analysis based on techniques in data science, statistics and/or microeconomics required. The post holder should have a track record of high-quality research related to hazard modelling and/or analysing impacts of disasters. You should have the ability to work with packages such as Stata/R, code accurately and methodically, be organised and communicate clearly in both writing and orally. Commitment to producing high quality research in a collaborative working environment essential.

Duties and responsibilities
- Data extraction, cleaning and preparation using longitudinal household survey data
- Developing and validating machine learning models that predict health costs for various hazards and disasters in Indonesia
- Meticulous documentation of methods and codes developed
- Literature reviews as required § Contribute to writing at least 1 journal article based on the research
- Contribute to organizing the SoFIT project webinar with international team § Work in an open and transparent way, developing ideas and analysis collaboratively with other team members including international partners
- Contribute to the project communications strategy through policy briefs, presentations at webinars and seminars
- Actively follow UCL policies including Equal Opportunities and Equality policies
- Maintain an awareness of and observe Fire and Health & Safety Regulations.

What we offer

As well as the exciting opportunities this role presents, we also offer some great benefits some of which are:
• 41 Days holiday (27 days annual leave 8 bank holiday and 6 closure days per annum) per annum
• Additional 5 days' annual leave purchase scheme
• Defined benefit career average revalued earnings pension scheme (CARE)
• Cycle to work scheme and season ticket loan
• Immigration loan
• Relocation scheme for certain posts
• On-site gym
• Enhanced maternity, paternity and adoption pay
• Employee assistance programme: Staff Support Service
• Discounted medical insurance. To find out more, visit