Thom Laepple writes:

I would like to draw your attention to the opening of two senior scientist and two postdoc positions in the Polar Terrestrial Environmental Systems section to complement the Earth System Diagnostics Team at the AWI (http://www.awi.de/) research centre in Potsdam, Germany

We are offering

One position for a statistician (with tenure track option) to optimally interpret complex and small sample size environmental datasets (such as paleoclimate data)

Statistician climate/environmental data

One position for a senior scientist on theoretical and stochastic modelling of Earth System processes (climate & paleoclimate archives)

https://recruitingapp-5442.de.umantis.com/Vacancies/960/Description/2

Further, we are offering two two year PostDoc positions related to the ERC Starting Grant SPACE (Space time structure of climate change) of T. Laepple

Postdoc in ice-core research / statistical data analysis (m/f/d)

https://recruitingapp-5442.de.umantis.com/Vacancies/973/Description/2

Ideally, the candidate has experience with time-series analysis in the time and spectral domain and ice-core data.

Postdoc in tree-ring research / tree ring data analysis

https://recruitingapp-5442.de.umantis.com/Vacancies/974/Description/2

Ideally, the candidate has experience in the analysis of large-scale tree ring networks

Here’s some description from the above links:

You will develop and apply statistical tools to optimally interpret complex and small sample size environmental datasets. One example is the reconstruction of climate fields from sparse paleoclimate proxy measurements from ice-cores and sediment cores. You will further teach and consult researchers at AWI on statistical analysis. Ideally, you will successfully apply for a third-party funded junior research group to further boost the topic of climate/environmental data statistics@AWI.

You will:
– Develop and apply Bayesian calibrations of environmental proxies to translate raw proxy ‘sensor’ data into physical/biological quantities
– Develop and apply field reconstructions from sparse and time uncertain data that allows to integrate proxy ‘sensor’ data and climate fields.
– Implement prototypes of digital tools such as proxy forward models / artificial core generators that can be integrated in O2A
– Design optimal sampling and measurement procedures.

Looks interesting.