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, Malaria and other Infectious Diseases, Maternal, Child and reproductive Health, Urban Health and Child and environmental health, Climate & Non-Communicable Diseases. ISGlobal is accredited with the Severo Ochoa distinction, a seal of excellence of the Spanish Science Ministry.
What We Are Looking for
We are recruiting an enthusiastic, self-motivated Statistician/Data Scientist to join our dynamic team in the Urban Environment and Air Pollution research programme. The statistician will be involved in several projects related to air pollution, urban environments and health, especially EXPANSE (EXposome Powered tools for healthy living in urbAN Settings – a project who has received funding from the European Union’s Horizon 2020 research and innovation programme under Grant Agreement No 874627) and CATALYSE (Climate Action To Advance HeaLthY Societies in Europe)- a project who has received funding from the European Union’s Horizon 2020 research and innovation programme under Grant Agreement No 874627).
The staff will be based in the research group of Cathryn Tonne, Associate Research Professor.
- Agricultural sciences
- Biological sciences
- Computer science
- Environmental science
- Ethics in health sciences
- Medical sciences
- Pharmacological sciences
Training and experience /Qualifications
- Higher education in Biostatistics or similar.
- Knowledge of applied and theoretical statistics.
- Programming in R using the main statistical tools and packages: dplyr, ggplot2, survival, mgcv, lme4.
- Experience with relational databases (SQL) and version-control systems (git/GitHub).
- Experience with mixed models for repeated measures data.
- Experience with survival analysis.
- Experience with dimensionality reduction techniques and clustering
- Experience with spatial statistics.
- Experience with basic Unix shell commands.
- Excellent organizational skills and comfortable working in a multi-disciplinary, multi-cultural team.
- Professional attitude and excellent attention to detail.
- Good communication skills both written and spoken.
- Good level of English (written and spoken).
The position will involve statistical analysis of environmental exposure data, application of regression models commonly used in epidemiology, and contributing to scientific publications. The role requires close collaboration with international project partners from a range of disciplines as well as researchers at ISGlobal.
The statistician/data scientist will work with large datasets from multiple sources including among others: measured and modelled ambient air pollution, personal exposure to air pollution, temperature, GPS tracks, among other data sources with varying spatial and temporal structure. The successful candidate will conduct analyses based on mixtures of exposures and application of dimension reduction techniques.
- Conducting data analysis in R
- Data curation
- Contributing to presentation of results
- Contribute to publications, reports, and grant applications.
- Provide statistical support to the researchers of the team.
- Plan and execute management of datasets.
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 .
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 .
- Good level of English and Spanish
- Duration: At least until 31/08/2022
- Starting date: ASAP
- Contract: (part or full time) FULL TIME
- Salary Range: According to profile and experience
During the crisis caused by COVID19, standard working conditions will be adapted to sanitary requirements.
The selection process is designed in two phases:
Interview phase of a technical nature, with the team that requires the incorporation. To assess the person’s skills and CV.
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.
How to apply
Applicants must fill in the request form and include the following code reference position: Statistician_EXPANSE_Jul22, attach the CV and a Cover Letter. Each attached document must be named with the candidate name and surname.
The receipt of applications will be open until 05th of August 2022.
Applications will be accepted until 17.00 CET of the closing date.
Only the applications submitted through the request form will be considered.
Only shortlisted candidates will be contacted.
The interviews could be placed during the reception candidatures period.
Diverse candidacies are welcome, that includes: gender, race, ethnicity, religion, age, sexual orientation, physical abilities, and political views.
More information: link