Experience/skills required:
We are looking for an individual who can support strategic activities related to integrated data science and collaborative, integrated modelling on the semantic web (semantic meta-modelling).
The selected candidate will:
Contribute to the ARIES (ARtificial Intelligence for Environment and Sustainability) platform, a semantic web infrastructure that uses artificial intelligence (AI) to build computational solutions to environmental, policy and sustainability problems. This technology, based on machine reasoning, machine learning, distributed computing and high-performance, multi-disciplinary and multi-paradigm system modelling, is the flagship product of the Integrated Modelling Partnership (IMP) which is expected to serve a growing number of worldwide users (from academia, governments, NGOs and industry) in the years to come.
The selected candidate should have:
- Strong analytical skills and an ability to learn quickly and to think outside the box. Our work is very innovative and you should expect your job to be as intellectually challenging as rewarding. A strong motivation and a desire to learn and explore new technologies are a must.
- Excellent interpersonal and communication skills.
- Excellent written and oral command of English.
- A degree in Computer Science, Ecology, Geography, Engineering, or other fields of relevance to Ecoinformatics.
- A working knowledge of geomatics and, in particular, open source GIS: OGC services, Geotools, Geoserver, etc.
- A strong background in data management, along with programming skills (any language and in particular Python, Java, R and Julia).
- Experience with database management systems such as PostgreSQL.
- Familiarity with Docker containers and deploying production software.
- Full fluency with Git and Maven technologies across the entire build-test-release cycle.
- Experience with an agile development process with industry-standard issue tracking, continuous development and deployment (BC3 uses the Atlassian toolchain: Jira, Bamboo, Confluence).
- Experience with machine learning will be an asset.
- An ability to work independently, with a diverse, multi-location and multi-lingual team.