During the past decade, the RL has envisioned and built the ARIES (ARtificial Intelligence for Environment and Sustainability platform), a technology that integrates network-available data and model components through semantics and machine reasoning.
Its underlying open-source software (k.LAB ) handles the full end-to-end process of integrating data and with multiple model integration types to predict complex change. It also supports selection of the most appropriate data and models using cloud technology and following an open data paradigm: the resulting insight remains open and available to society at large, and becomes a base for further computations, contributing to an ever-increasing knowledge base. For the first time, it is possible to consistently characterize and publish data and models for their integration in predictive models, building and field-testing technologies that have eluded researchers to date.
We are looking for an individual who can support strategic activities related to integrated data science and collaborative, integrated modeling on the semantic web (semantic meta-modeling).
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 modeling, 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.
Initial Tasks:
- 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. Experience in knowledge dissemination.
- Excellent written and oral command of English.
- A degree in Computer Science, Environmental Sciences, Engineering, or other fields of relevance to Ecoinformatics.
- A working knowledge of geomatics and in particular open source GIS: OGC services, Geotools, Geoserver, QGIS etc.
- A working knowledge or degree related to Remote Sensing.
- A strong background in data management, along with programming skills (any language and in particular Python or R). Experience with database management systems such as PostgreSQL.
- Experience with semantics programming and machine reasoning knowledge (any language and software, in particular k.LAB technology and k.IM language).
- Familiarity with the ARIES environment.
- Full fluency with Git technologies and Docker containers.
- 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.
Implied subtasks:
- Build modeling process: from data cleaning to interpretation of the model results.
- Interpret the resources and images from different platforms (RS).
- Write in semantics (k.IM language).
- Understand how the k.LAB modeling works.
- Profiling code execution.
After 4 months the candidate is expected to:
- Collaborate on developing, strengthening and debugging the GIS and remote sensing process and issues.
- Collaborate on the definition of unit tests and code review policies for both k.LAB and the associated data/model products.
- Participate in all aspects of the collection, cleaning, analysis, model building and deployment of modeling and data science process in k.LAB technology.
- Communicate and coordinate with both technical and non-technical stakeholders.
