The Barcelona Institute for Global Health (ISGlobal) is a cutting-edge institute addressing global public health challenges through research, translation into policy, and education. ISGlobal has a broad portfolio in communicable and non-communicable diseases including environmental and climate determinants, and applies a multidisciplinary scientific approach ranging from the molecular to the population level. Research is organized in the following main areas: Climate, Air Pollution, Nature and Urban Health; Environment and Health over the Lifecourse; Global Viral and Bacterial Infections; Malaria and Neglected Parasitic Diseases; Maternal, Child and Reproductive Health.
ISGlobal is accredited with the Severo Ochoa distinction (received the first accreditation in 2019 and renewed it in 2024), a seal of excellence of the Spanish Science Ministry.
Context and MissionIn the framework of our Centre for Excellence Severo Ochoa Programme (CEX2023-001290-S), we are currently seeking an enthusiastic, self-motivated post-doctoral epidemiologist with expertise in Data Science and Machine Learning to join our team, which focuses on analyzing weather data and its connections to both infectious and non-infectious diseases. This position is central to our innovative project combining weather forecasts, epidemiological models, and machine learning to develop early warning systems for health risks associated with environmental factors.
The successful candidate will work within two pioneering platforms, Forecaster-Dot-Health and Famba:
Famba (https://web.Fambaproject.Com/): Initially developed as a health monitoring platform for international travelers, Famba now gathers health, mobility, and climate data to identify and track emerging infections on a global scale, strengthening preparedness for future pandemics. The postdoctoral selected candidate will play a pivotal role in extending the Forecaster-Dot-Health and Famba platforms to cover new health risks, geographic regions, and forecast durations. This post-doctoral role offers a unique opportunity to apply advanced data science techniques and epidemiological models to weather and climate data, impacting both infectious and chronic disease forecasting. The selected candidate will automate the acquisition and processing of weather and climate forecasts, and collaborate with scientific teams to leverage these data for health-related studies.
The postdoctoral researcher will also ensure that weather and climate forecasts are readily available and integrated into scientific studies across the institution, fostering collaboration and driving new discoveries in health and environmental science. The researcher will work closely with Prof. Joan Ballester, Prof. Jose Muñoz, and Prof. Paula Petrone.
#J-18808-Ljbffr