Postdoctoral in Accounting of Social and Natural Capital
The RL generates multidisciplinary scientific knowledge from human-nature interdependence to address complex sustainability problems through artificial intelligence (AI). The goal of the RL is to provide data, models and understanding by retrieving, evaluating and integrating the existing information in order to support an effective policy-making where nature counts. During the past decade, the RL has envisioned and built the ARIES (ARtificial Intelligence for Environment and Sustainability (https://aries.integratedmodelling.org/) platform, a technology that integrates network-available data and model components through semantics and machine reasoning. Its underlying open-source software (k.LAB, https://docs.integratedmodelling.org/technote/) handles the full end-to-end process of integrating data with multiple model integration types.
In 2021, the UN Statistical Commission adopted the System of Environmental Economic Accounting Ecosystem Accounting (SEEA EA) as an international statistical standard and encouraged countries to implement the SEEA EA. A global SEEA EA implementation strategy has been developed to rapidly expand the number of countries compiling natural capital accounts (NCA) based on the SEEA. The overall implementation strategy includes capacity building, development and guidelines, strengthening collaboration as well as development of supporting data and tools. The development of ARIES for SEEA, a collaboration between the United Nations Statistical Division (UNSD) and BC3, started in April 2020. Its development is undertaken by a Sector Hub, which reports to the UN Committee of Experts on Big Data and Data Science for Official Statistics, and which collaborates on the UN Global Platform, a cloud-service platform supporting international collaboration in the development of official statistics using new data sources and innovative methods. Since then, the ARIES team has been collaborating with important institutions to advance the work in NCA, including engaging with National Statistic Offices to help compile environmental accounts, and our team has been commissioned to diverse projects from worldwide institutions, such as the European Space Agency to integrate remote sensing data in the system, and the World Bank, to perform different environmental economic analyses.
Key responsibilities:
The postdoctoral researcher will participate in:
Contribute to the ARIES platform, and its applications in accounting at different scales of application – e.g. businesses, regions ad nations – and in different domains of knowledge, e.g. ecological and socio-economics modeling.
Have backgrounds and interests in the broad areas of Statistics ranging from theoretical focus to applications in domains related to environmental assessment, such as Engineering, Management, Science, Life Science and Social Science. Duties will include performing independent research in statistics and leading activities within the ARIES mission.
Work with external collaborators, including UNSD, World Bank, European Space Agency and statistical agencies to align innovation and research with accounting standards.
Desired skills:
Experience in statistical modelling: a combination of theoretical and empirical experience is well appreciated.
Demonstrated experience in the collection, compilation, analysis and dissemination of data, previous experience in geospatial explicit analysis is desirable.
Awareness of optimization techniques and experience with different problems and domains, ideally in spatial applications.
Familiarity with traditional Machine Learning models (k-means, KNN, decision trees, SVM, Bayesian/graphical models, Gaussian process, etc.) is desirable, but not an excluding factor.
Ability to work in different coding environments (local, notebooks, containers) and familiar with software engineering workflows (testing, code management/Git) – candidates with experience using multiple toolkits or platforms are preferred.
Handling of large data sets and models on distributed file systems is desirable, but not an excluding factor.
Additional experience/skills required:
A PhD in Statistics, Computational Social Science, Computer Science, Physics, Mathematics, Engineering, Geography or other fields relevant to the position.
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.
Object-oriented programming ability is considered a very valuable asset. In case there is no experience with this, the candidate should be eager to learn these skills.
Good interpersonal and communication skills.
Good written and oral command of English.
Ability to work independently, with a diverse team.
Benefits and work environment:
Interdisciplinary and inspiring work environment
Quiet and spacious workspaces
Possibility of participating in internal training and academic activities of the center35-hour week work calendar
30 days of vacation per year