Postdoc Researcher (m/f/d) in Data Science and Bayesian Network Technology
The department of Biogeochemical Modeling / Applied Modeling and Quantitative Methods at the Institute of Carbon Cycles offers a vacant position for a Postdoc researcher in the field of Data Science and Bayesian Network Technology.
You will establish yourself as a data scientist in the EU Horizon 2020 project ECOTIP and conduct applied transdisciplinary research on the effects of climate change and anthropogenic pressures on key marine ecosystem services and socio-ecological systems in Artic environments. As such, you will engage with leading experts of Artic research to promote science of high public interest, including ocean carbon sequestration, biodiversity and sustainable fisheries. The open position has a fixed term contract of max. 24 months and is to be filled as soon as possible, but no later than May ’22. Remuneration will depend on qualification.
Your tasks:
Your role is to solve complex inference problems with data. Use data scientific tools to find solutions for integrating environmental, socio-economic and socio-cultural data with a focus on probabilistic reasoning and quantification of uncertainty. This involves the co-creation of Bayesian Belief Networks (BBNs) as a means to improve system understanding, identify knowledge and data gaps, enable exploratory and scenario analysis, assess system resilience and adaptive capacities and communicate risks and policy recommendations. Therefore, you will actively participate in different ECOTIP task groups to advance the team’s skills with your expertise and thus, to help deliver on the project’s data analysis and dissemination strategy. In addition, you are expected to actively engage with ECOTIP stakeholders and contribute to the project’s scientific reporting and outreach by supporting the implementation of BBN web-apps (e.g., Shiny).
Your profile:
Applicants required a PhD in computer sciences, applied mathematics, bioinformatics or related disciplines with a minimum of 2 years of relevant experience in a data science environment. A background in marine environmental sciences and/or integrated ecosystem assessments would be beneficial.
Further crucial skills are:
- expert knowledge and hands-on experience in Bayesian network technology, probabilistic graphical models, Gaussian processes and/or MCMC
- ability to structure and reduce complexity
- proven track record in delivering data science products from idea to deployment
- ability to work closely with non-technical teams
- confidence in handling scientific data and experience in data preparation, data modeling, analysis and visualization
- strong coding skills in scripting languages
- high confidence in verbal and written communication
- fluent in English; German language skill is a plus