Research Associate DA And ML in Oceans

Job summary

To undertake and disseminate internationally leading research into the development of a range of the next generation data assimilation with machine learning models and applications to ocean modelling problems in the project “Drone/UAV based imaging combined with deep learning and data assimilation to support the ongoing development of the tidal energy sector”. The Research Associate will collaborate with and strengthen the...

Job listing information

  • Reference ENG00901
  • Date posted 11 July 2019
  • Closing date 28 July 2019

Job description

Job summary

To undertake and disseminate internationally leading research into the development of a range of the next generation data assimilation with machine learning models and applications to ocean modelling problems in the project “Drone/UAV based imaging combined with deep learning and data assimilation to support the ongoing development of the tidal energy sector”. The Research Associate will collaborate with and strengthen the multi-disciplinary team of researchers already in place working on closely related projects. Ultimately the post holder will contribute to the delivery of an observational system capturing data from drones and that could be applied in principle to any coastal site.

Duties and responsibilities

• Plan and carry out research in the project “Drone/UAV based imaging combined with deep learning and data assimilation to support the ongoing development of the tidal energy sector”
• Undertake internationally leading research into the development of advanced techniques for data assimilation, deep learning (convolutional or recurrent neural networks perhaps) to get info on tidal jets, vortices etc.
• Plan and carry out research in accordance with the project aims and under instruction from the project investigators.
• To take initiatives in the planning of research.
• To direct the work of small research teams.
• To identify and develop suitable techniques, and apparatus, for the collection and analysis of data.
• To conduct data analysis.
• To ensure the validity and reliability of data at all times.
• To maintain accurate and complete records of all findings.
• To write reports for submission to research sponsors.
• To present findings to colleagues and at conferences.
• To submit publications to refereed journals.
• To provide guidance to staff and students.
• To attend relevant workshops and conferences as necessary.
• To develop contacts and research collaborations within the College and the wider community.
• To promote the reputation of the Group, the Department and the College.
• To provide guidance to PhD Students.
• Contribute to bids for research grants.

Essential requirements

A PhD (or equivalent) in an area pertinent to the research subject e.g. Mathematics, Physics, Computing, Engineering.

Background in computational science, in particular optimisation, data analysis, and data assimilation techniques (adjoint, enKF etc)

Experience of implementation of data assimilation techniques within complex multi-physics models, and in particular fluid dynamics.

Experience of modern programming in languages including Fortran, C++ and Python.

Experience working within substantial scientific computational projects and large multi-disciplinary environments.
Knowledge of the theoretical development and coding of methods for the numerical solution of systems of PDEs.

Theoretical understanding of finite element/volume methods and numerical linear algebra.

Knowledge of MPI programming and HPC platforms.


Further information

To apply, visit www.imperial.ac.uk/jobs and search by the job reference ENG00901

Should you require any further details on the role please contact: Fay Miller, DSI Research Group Administrator: f.miller@imperial.ac.uk

For technical issues when applying online please email recruitment@imperial.ac.uk



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Additional information

Please note that job descriptions cannot be exhaustive and the post-holder may be required to undertake other duties, which are broadly in line with the above key responsibilities.

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