PhD position “Digital Ice-Cores; Paleo-Climate reconstruction using Bayesian modeling” – Deadline 23 September 2022
To understand future climate change, it is critical to fully understand the past and present climate system. Information about this is encrypted in paleoclimate archives such as ice- cores or bore-hole temperatures reflecting the temperature of glaciers such as Antarctica. However, it is difﬁcult to de-convolve and combine this knowledge as proxy records are often time-uncertain, are noisy, sparse and record the climate in very different ways.
Recently, there have been advances in understanding the ice-core recording process. Based on this, proxy system models enabling the production of “digital” cores from climate model simulations, i.e. numerical forward models, were developed. Further,
bore-hole temperatures and isotope data deliver complementary information. Still, the challenge to optimally invert the process from the climate to the ice-core record and to reconstruct the climate state from such sparse, noisy and diverse data is largely unresolved.
This PhD project aims to improve on the borehole inversion methods as well as on the climate field reconstruction technique by means of modern techniques in numerical modeling and Bayesian inference to optimally combine the various information sources. In collaboration with data science and statistics experts and experts from paleo-climate research, this project aims to develop and test a new reconstruction technique that could
provide a better quantitative access of paleo-climate data and insight into the past climate evolution.
- Set up, i.e. discretize and efficiently implement forward models, given by advection diffusion equations, for glacier bore-hole temperature profiles
- Develop and test inversion methods for the relationship of water isotopes and temperature using Bayesian inference
- Use advanced Bayesian hierarchical modeling techniques to combine the information from water-isotopes and borehole temperatures to reconstruct the local temperature evolution. Ideally, this will be extended to spatio-temporal field reconstructions making use of the spatial physical covariance structure from reanalysis data. You will test this model using surrogate data from simulated (‘digital’) ice-cores
- Based on simulated cores and the developed framework, you will optimize the sampling strategy and show the feasibility and limitations of combined isotope and borehole thermometry to reconstruct the temperature evolution of Antarctica.
- A degree (Master, Diploma) in mathematics, computer science, physics, climate sciences, or a related field
- Strong analytical, mathematical and statistical skills
- Proficiency in a programming language (preferably Python or C/C++)
- Excellent English language skills, both written and spoken
Additional skills and knowledge
- Experience in numerical analysis and Bayesian methods is a benefit
- Previous experience with ice-cores or (paleo)climate research is an advantage.
Please contact Thomas Laepple (firstname.lastname@example.org) or Peter Zaspel (email@example.com) for further information.
This position is limited to 3 years. The salary will be paid in accordance with the Collective Agreement for the Public Service of the Federation (Tarifvertrag des öffentlichen Dienstes, TVöD Bund), up to salary level 13 (100%). The place of employment will be the Jacobs University Bremen
You will participate in the Helmholtz School for Marine Data Science MarDATA (https://www.mardata.de).
The AWI is characterised by
- our scientific success – excellent research
- collaboration and cooperation – intra-institute, national and international, interdisciplinary
- opportunities to develop – on the job, aiming at other positions and beyond AWI
- a culture of reconciling work and family – an audited and well-supported aspect of our operation
- our outstanding research infrastructure – ships, stations, aircraft, laboratories and more
- an international environment – everyday contacts with people from all over the world
- having an influence – fundamental research with social and political relevance
- flat hierarchies – facilitating freedom and responsibility
- exciting science topics, with opportunities also in technology, administration and infrastructure
Equal opportunities are an integral part of our personnel policy. The AWI aims to increase the number of female employees and therefore strongly encourages qualified women to apply.
Disabled applicants will be given preference when equal qualifications are present.
The AWI fosters the compatibility of work and family in various ways and has received a number of awards as a result of this engagement.
Please submit your application by September 23th 2022, exclusively online.
Reference number 22/148/D/Geo-bShort listed candidates will be invited for a job interview on the September 30th 2022.
The preferred starting date would be Nov/Dec 2022.
Further information can be found in this link.