Research Associate in Stochastic Parameterization of Ocean Turbulence for Observational Networks
Imperial College London Department of Mathematics
United Kingdom

Job summary

Applicants are invited for a Research Associate position in the Department of Mathematics at Imperial College London (ICL).  The position is funded by a US Office of Naval Research and can be extended to 36 months. The project involves an interdisciplinary effort bringing together stochastic mathematical modelling and data analysis, geophysical fluid dynamics, and novel ocean modelling with the goal of furthering our understanding and...

Job listing information

  • Reference NAT01264
  • Date posted 13 September 2022
  • Closing date 13 November 2022

Key information about the role

  • Location South Kensington Campus - Hybrid
  • Position type Full time, fixed term
  • Salary £43,093 – £50,834 plus benefits
  • Department Department of Mathematics
  • Category Researcher / Non Clinical Researcher

Job description

Job summary

Applicants are invited for a Research Associate position in the Department of Mathematics at Imperial College London (ICL).  The position is funded by a US Office of Naval Research and can be extended to 36 months. The project involves an interdisciplinary effort bringing together stochastic mathematical modelling and data analysis, geophysical fluid dynamics, and novel ocean modelling with the goal of furthering our understanding and parameterization of unresolved dynamics (submesoscales, internal waves, etc) in operational ocean/climate models. The project also has a strong observational flavour both in terms of project definition and the desirable outcomes.

Duties and responsibilities

You will be involved in the theoretical development of variational models of ocean dynamics and rough paths and will work with data from realistic and idealized simulations to implement and test the new theoretical (stochastic) approach to representing unresolved dynamics.  You will also collaborate with other team members, numerous PhD students, and the aforementioned network of collaborators in developing research advances related to the goals of this grant.

Essential requirements

    • Hold a PhD (or equivalent) in Nonlinear Science, especially in Geophysical Fluid Dynamics (GFD) or a closely related discipline
    • A broad and strong background in the Derivation, Analysis and Computational Simulation of Mathematical Models in Nonlinear Science, especially in GFD for physical oceanography
    • Sufficient interest and knowledge of Stochastic GFD to competently explain how Kelvin’s circulation theorem relates to smooth invertible transformations, Lie derivatives, stochastic variational principles and computational methods for SPOT-ON
    • Expertise and refereed publications in Physical Oceanography relevant to SPOT-ON
    • Expertise and refereed publications on Stochastic Partial Differential Equations (SPDE)
    • A track record of independent research in SPDE modelling and computational simulation
    • Experience with programming in Firedrake
    • Experience in giving talks at internationally recognised conferences and workshops
    • Experience with applications of Machine Learning tools
    • Ability to keep accurate records of research results and activity, help with reporting
    • Ability to work effectively with a team of researchers and across disciplines
    • Ability to direct the work of a small research team and motivate others to produce a high standard of work

Further information

Full details of the role can be found on the Job Description.

*Candidates who have not yet been officially awarded their PhD will be appointed as Research Assistant within the salary range £38,194- £41,388 per annum.

This is a full time and fixed term role for 24 months. Please note that the maximum salary on appointment can be £43,093.

For any specific queries regarding the post please contact Professor Darryl Holm, (d.holm@imperial.ac.uk)

The College is a proud signatory to the San-Francisco Declaration on Research Assessment (DORA), which means that in hiring and promotion decisions, we evaluate applicants on the quality of their work, not the journal impact factor where it is published. For more information, see https://www.imperial.ac.uk/research-and-innovation/about-imperial-research/research-evaluation/


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