Research Engineer – Computational Biology Group (RE2)
Context And Mission
The Computational Biology Group (http://life.bsc.es/compbio), within the Life Sciences Department at the BSC, is involved in multiple projects covering several areas of precision medicine, systems biology, network science, and epidemiology.
The Computational Biology group, led by ICREA professor Alfonso Valencia, is looking for a Researcher Engineer to join a national-founded research project called “MePreCiSa - Precision Medicine for Healthy Cities”.
MePreCiSa aims to develop a Cloud platform for integrated health assessment in cities and their inhabitants, following an approach based on Big Data analogous to that used in precision medicine. The central axis of the proposal will be the use of mobility data based on mobile phones that allow considering the mobility patterns of the population for the generation of dynamic indicators of exposure, contact and risk, which will be designed and used in the analysis of different use cases. The use cases include the interdisciplinary study of the impact of mobility factors, environmental quality and socio-economic determinants on the well-being and health of citizens, including respiratory diseases, allergies, and mental and cardiovascular diseases; the extension of a mobility-based epidemiological model to simulate real epidemic spread scenarios; the use of population dynamic indicators in the analysis of biomarkers obtained in wastewater.
The Researcher Engineer will work in a highly sophisticated High-Performance Computing (HPC) environment, have access to state-of-the-art systems and computational infrastructures, and establish collaborations with international and local experts in different areas of biomedical research. In particular, the candidate will work in collaboration with senior researchers.
- Data integration and API development.mobility data.
- Develop methods to integrate and mine epidemic and mobility data to discover spreading patterns.
- Design and implement tools that facilitate access to the data as well as the automatic generation of summary dashboards.
- Implementation and calibration of epidemic models using optimization simulation approaches.
- Participate in writing scientific articles, blogs, and online media posts.
- Participate in internal group meetings and other scientific discussions.
- Degree in Computer Science, Data analysis or related discipline.
- A Master's degree in Computer Science, Data Analysis or a related discipline is also valuable.
Essential Knowledge and Professional Experience
- Programming: Python, R, Julia, Matlab, Java, C++, or similar
- Experience in software development practises (documentation, version control, etc)
- Experience in Frontend/Backend develpment
- Experiences in Unix/Linux systems
- Experiences in Databases (e.g. MySQL, MariaSQL, PostgreSQL, MongoDB)
Additional Knowledge and Professional Experience
- Experience in at least one of the following:
o Python tool for data science (e.g., Pandas, Scikit-learn, Matplotlib/Seaborn)
o R tool for data science (e.g., Pandas, Scikit-learn, Matplotlib/Seaborn)
o Experience with Network Analysis tools (Networkx/igraph, Gephi, yEd).
- Experience developing Interactive Dashboards using, Plolty, Dash, Shinny or similar
- Experiences in software containerization (e.g. Docker, Singularity, etc)
- Interest in the Life Sciences area, in particular epidemiology and urban modeling
- Fluency in spoken and written English
Capacity to explore and exploit new research lines
Good communication and presentation skills
Ability to work both independently and within a team