Deep Learning for Modeling Ocean–Ice Shelf Interactions (M/F)

Job Description

Missions

The overall objective is to improve the integration of polar ice sheets into Earth system models by using neural network emulators at the interface between an Antarctic ice sheet model (Elmer/Ice) and a global ocean model (NEMO). The selected candidate will contribute to the ANR-AIAI project (https://anr-aiai.github.io).

Scientific Context
The melting of Antarctic ice shelves by the ocean is a major source of uncertainty regarding global climate change and sea level rise. Accurately representing ice-ocean interactions beneath ice shelves is a major challenge due to the coarse spatial resolution of climate models. Simple parameterizations exist to represent melting beneath unresolved or partially resolved ice shelves, but they generally fail to capture the complexity of the response to changing ocean conditions (Burgard et al., 2022). The application of deep learning to this problem has yielded promising results (Rosier et al., 2023; Burgard et al., 2023). Further development and refinement of these techniques should therefore significantly improve the representation of basal melting in simulations.

Activity

• Develop a neural network interface to simulate subglacial melting in the NEMO ocean model.
• Present the results at international conferences.
• Participate in the AIAI project and IGE activities (meetings, seminars, etc.).
• Keep up to date with publications on the subject and write scientific articles

Your Profil

Skills

Selection will be based on the following scientific and technical criteria:
• Proven experience with deep learning methods.
• Proven experience with Python programming.
• Proven experience in writing scientific papers.
• General knowledge of physical oceanography or climate dynamics.
The selection committee will take gender balance within the research team into account.

Your Work Environment

The successful candidate will be assigned to the Institute of Environmental Geosciences (IGE). This is a public research laboratory under the supervision of the CNRS, the IRD, the University of Grenoble Alpes, Grenoble-INP, and INRAE, which focuses on climate change and human impact on our planet in polar, mountain, and intertropical regions—areas that are particularly sensitive and face major societal challenges. It brings together approximately 300 people, including more than 180 permanent staff members (researchers, faculty-researchers, engineers, and technicians) and approximately 120 staff on fixed-term contracts (doctoral students, researchers, and IT staff). The laboratory also hosts several dozen interns and visiting scientists each year. The laboratory is located at three sites on the Grenoble university campus, all within a few minutes' walk of each other. The IGE is one of the main laboratories of the Grenoble Observatory of Universe Sciences (OSUG), a federative structure of the INSU. The successful candidate will join the CryoDyn team, which focuses on ice dynamics and their connections to the climate system. This person will be supervised by Nicolas Jourdain (IGE) and Clara Burgard (IPSL-LOCEAN, Paris). There will be close collaboration with IPSL-LSCE (Cécile Agosta).

Compensation and benefits

Compensation

between €3,041.58 and €4,651.78, depending on experience

Annual leave and RTT

44 jours

Remote Working practice and compensation

Pratique et indemnisation du TT

Transport

Prise en charge à 75% du coût et forfait mobilité durable jusqu’à 300€

About the offer

About the CNRS

The CNRS is a major player in fundamental research on a global scale. The CNRS is the only French organization active in all scientific fields. Its unique position as a multi-specialist allows it to bring together different disciplines to address the most important challenges of the contemporary world, in connection with the actors of change.

CNRS

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