Job Board Title:
Postdoctoral position: Early warning systems of infectious and non-communicable diseases
Post Date
11/14/2024
Expiration Date
12/14/2024
Details:
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 MISSION
In 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:
Forecaster-Dot-Health (https://forecaster.health/): A cutting-edge platform that transforms real-time weather and air pollution forecasts into early warning systems, predicting the health impacts of heat, cold, and air pollutants based on age, sex, and cause of death. Circumscribed within the PR3 hub (https://www.isglobal.org/en/-/isglobal-impulsa-un-hub-de-preparacion-ante-crisis), we aim to scale this system to cover a wider array of infectious and non-communicable diseases, geographical areas, and forecast lead times.
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.
This position will be supported by funding from the “Centro de Excelencia Severo Ochoa 2024-2028” Program (CEX 2023-0001290-S) from the Spanish Ministry of Science and Innovation, and the Spanish Research State Agency (MCIN/AEI/10.13039/501100011033).
TRAINING AND EXPERIENCE / QUALIFICATIONS
PhD (or equivalent) in epidemiology, environmental health, data science or related discipline
Expertise in Data Science and Machine Learning with background in weather data, infectious diseases, and epidemiology (see below for specific technical competences)
Motivated, self-directed researcher capable of setting and meeting deadlines and delivering research outputs
Strong organization and team-working skills
Effective verbal and written communication skills; strong communication skills to collaborate effectively with interdisciplinary teams and act as a resource for other researchers
Proficiency in English (written and spoken)
SPECIFIC TECHNICAL COMPETENCES
Desirable:
Strong experience with Linux environments and scripting languages such as Python and R.
Proficiency in data science and machine learning techniques, particularly related to climate and health data.
Solid understanding of weather data analysis and subseasonal-to-seasonal climate forecasts, including knowledge of meteorological datasets (e.g., reanalysis data, ensemble forecasts).
Experience with epidemiological modeling and its application to health risk assessment.
Familiarity with the management and integration of diverse datasets, including health, climate, and environmental data.
Optional:
Experience with Shiny for creating interactive web applications.
Prior experience in developing and implementing early warning systems based on climate forecasts.
Knowledge of chronic disease epidemiology and its relationship with climate factors (specific focus can be discussed based on ongoing research initiatives).
Expertise in spatial analysis, GIS tools, and handling large-scale geospatial datasets.
KEY RESPONSABILITIES
Design and implement automated routines to schedule, download, and process weather and subseasonal-to-seasonal climate forecasts.
Apply epidemiological models to forecast weather impacts on public health, particularly in relation to infectious and non-communicable diseases.
Use machine learning to enhance forecast accuracy and develop early warning systems for health risks.
Serve as a technical liaison for the institution’s research staff, providing expertise and support in the use of weather and health data.
Collaborate with scientific teams to ensure the integration of weather and health models into a broad range of studies, expanding the geographic and disease coverage of the platforms.
AUXILIAR TASKS
This job description reflects the present requirements of the post but may evolve at any time in the future as duties and responsibilities change and/or develop providing there is appropriate consultation with the post-holder.
This job description is not a definitive or exhaustive list of responsibilities but identifies the key responsibilities and tasks of the post holder. The specific objectives of the post holder will be subject to review as part of the individual professional assessment process.
SKILLS
Good interpersonal, communication, presentation, and academic writing skills and ability to work independently.
The post holder will adhere to ISGlobal principles contained in People management policy, including Equity, diversity and health safety. The post holder will respect, and accountable to ensure ISGlobal policies and procedures.
LANGUAGE LEVEL
Proficiency in English (written and spoken)
CONDITIONS
Duration: 3/4 years
Starting date: as soon as possible
Contract: (part or full time): Full time
Salary Range: According to experience and profile
HOW TO APPLY
Applicants must fill in the request form, attach the CV and a Cover Letter describing research interest and plans at ISGlobal. Each attached document must be named with the candidate name and surname.
The receipt of applications will be open until a candidate is selected.
Only the applications submitted through the request form will be considered.
Only shortlisted candidates will be contacted.
We welcome diverse candidates according to gender, race, ethnicity, religion, age, sexual orientation, physical abilities, and political views.
Please contact giulia.pollarolo@isglobal.org for questions about this position.
SELECTION PROCESS
The selection process is designed in two phases:
1- Interview phase of a technical nature, with the team that requires the incorporation. To assess the person\'s skills and CV.
2 - Meeting with HR with the finalist(s) to finish assessing the profile and discuss contractual and institutional issues.
If needed any technical test could be pass. A Psychological Competency Evaluation Test will be required for the structural or transversal positions.
In accordance with the OTM-R principles, a gender-balanced recruitment panel is formed for every vacancy at the beginning of the process. After reviewing the content of the applications, the panel will start the interviews, with at least one technical and one administrative interview. A profile questionnaire as well as a technical exercise may be required during the process.
Qualifications:
PhD (or equivalent) in epidemiology, environmental health, data science or related discipline
Expertise in Data Science and Machine Learning with background in weather data, infectious diseases, and epidemiology (see below for specific technical competences)
Motivated, self-directed researcher capable of setting and meeting deadlines and delivering research outputs
Strong organization and team-working skills
Effective verbal and written communication skills; strong communication skills to collaborate effectively with interdisciplinary teams and act as a resource for other researchers
Proficiency in English (written and spoken)
SPECIFIC TECHNICAL COMPETENCES
Desirable:
Strong experience with Linux environments and scripting languages such as Python and R.
Proficiency in data science and machine learning techniques, particularly related to climate and health data.
Solid understanding of weather data analysis and subseasonal-to-seasonal climate forecasts, including knowledge of meteorological datasets (e.g., reanalysis data, ensemble forecasts).
Experience with epidemiological modeling and its application to health risk assessment.
Familiarity with the management and integration of diverse datasets, including health, climate, and environmental data.
Optional:
Experience with Shiny for creating interactive web applications.
Prior experience in developing and implementing early warning systems based on climate forecasts.
Knowledge of chronic disease epidemiology and its relationship with climate factors (specific focus can be discussed based on ongoing research initiatives).
Expertise in spatial analysis, GIS tools, and handling large-scale geospatial datasets.
Employer:
ISGlobal
Contact:
Giulia Pollarolo
Address:
giulia.pollarolo@isglobal.org
job@isglobal.org
Work Phone:
932279892
Email:
giulia.pollarolo@isglobal.org
Website:
https://www.isglobal.org/en/-/postdoctoral-position-early-warning-systems-of-infectious-and-non-communicable-diseases