Bayi Glacier in Qilian Mountain, China (Credit: Xiaoming Wang, distributed via imaggeo.egu.eu)

Job advertisement PhD Studentship: Data Assimilation and Machine Learning to Emulate Sea Ice Thermodynamics

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European Geosciences Union

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PhD Studentship: Data Assimilation and Machine Learning to Emulate Sea Ice Thermodynamics

Position
PhD Studentship: Data Assimilation and Machine Learning to Emulate Sea Ice Thermodynamics

Employer
University of Reading logo

University of Reading

Homepage: http://www.reading.ac.uk/


Location
Reading, United Kingdom of Great Britain and Northern Ireland

Sector
Academic

Relevant divisions
Climate: Past, Present & Future (CL)
Nonlinear Processes in Geosciences (NP)
Ocean Sciences (OS)

Type
Full time

Level
Student / Graduate / Internship

Salary
Open

Required education
Master

Application deadline
30 May 2021

Posted
28 April 2021

Job description

We offer a PhD studentship under the supervision of Alberto Carrassi (n.a.carrassi@reading.ac.uk) within the international project “Scale-aware sea-ice project – SASIP” (https://sasip-climate.github.io/). The University of Reading will work to provide data constrained sea-ice analyses using data assimilation (DA) and machine learning (ML). The postholder will work on ML and DA for parameterization design, in close interaction with SASIP members at ENPC in France and at NERSC in Norway.

The student will focus on sea-ice thermodynamics, using hybrid DA-ML to emulate these processes and/or to generate data-driven parametrization of unresolved scales, with a 1-dimensional sea-ice. The PhD will contribute to devising data-driven parametrizations, or emulators, of the thermodynamics processes in the full sea-ice model under development in SASIP. The student will work on a cutting-edge theme at the crossroad between applied mathematics and climate science, contributing to the understanding of the fast-evolving processes in Arctic and to predict their impact. The work will be undertaken within an international project and the student will be immersed in a vibrant context whereby interacting with several scientists and other peer students and postdocs.

The research will be conducted with other members of SASIP and externally co-supervised by Laurent Bertino, Julien Brajard and Einar Olason at NERSC (Norway) and Marc Bocquet at ENPC (France). The student will have the opportunity to visit their premises. This recruitment is among the three at Reading within SASIP, including two Postdocs: they will all interact very closely and constitute SAPIP’s working group at Reading.

The postholder will be at the Dept of Meteorology within the Data Assimilation Research Centre (https://research.reading.ac.uk/metdarc), an international, diverse and stimulating environment. She/he will be also affiliated at the National Centre for Earth Observation (https://www.nceo.ac.uk/) a centre of over 100 scientists in the UK. The postholder will benefit from the ample offer of training at Reading and nationally within NCEO.

Eligibility:

- We expect you to have either a 1st or upper 2nd class degree, or a master’s with Distinction or Merit, in environmental science, applied mathematics, physics or computer sciences
- Desirable: Cryosphere physics, machine learning, data assimilation.
- This opportunity is open to candidates worldwide but only covers Tuition Fees at the UKRI rate. A successful international candidate would need to fund or secure sponsorship for the difference in the fees.

Funding Details:
- Starts 20/09/2021
- 3 years award
- Funding covers full tuition fees plus UKRI stipend


How to apply

Click at https://www.risisweb.reading.ac.uk/si/sits.urd/run/siw_ipp_lgn.login?process=siw_ipp_app&code1=P_ADM&code2=0001, create your account and use the link sent by email to start the application process. During the application process select the PhD in Atmosphere, Oceans and Climate, and upload transcripts, CV, certificates and in the “other’s” the motivation letter and the contacts of up to two referees.

Important notes

Quote the reference ‘GS21-041’ in the ‘Scholarships applied for’ box which appears within the Funding Section of your on-line application.