[ES_JOBS_NET] Job Vacancy at ECMWF for: Scientist - high resolution modelling

[Julie Palmer]

Dear Mailing list,

I am sharing the following job vacancy for:

Scientist - high resolution modelling
Position information

Vacancy No.: VN19-13

Department: Research

Grade: A2

Section: Earth System Modelling

Job Ref. No.: STF-PL/19-13

Reports to: Numerical methods team leader

Publication Date: 6 March 2019

Closing Date: 8 April 2019

About ECMWF
ECMWF is both a research institute and a 24/7 operational service, producing and disseminating numerical weather predictions to its Member States. ECMWF carries out scientific and technical research directed to the improvement of its forecasts, collects and processes large amounts of observations, and manages a long-term archive of meteorological data. Satellite and in situ observations provide the information for up-to-date global analyses and climate reanalyses of the atmosphere, ocean and land surface.

For details, see www.ecmwf.int/<http://www.ecmwf.int/>.

ECMWF uses its high-performance computing (HPC) facility to produce a time-critical twice-daily numerical weather forecast. Given the expected need for increasing the resolution and complexity of the weather forecast model, new approaches to improve efficiency of global simulations, such as mixed precision or the application of tools from deep learning, need to be evaluated for potential use in operational weather forecasts.
Summary of the role
We are now looking to recruit a Scientist who will work towards a coupled atmosphere/ocean model at ECMWF that can run at unprecedented levels of spatial and temporal resolution.
A focus will be on the development of a testbed for high resolution ocean models to identify and quantify the fidelity of simulations when parameters, boundary conditions or numerical precision are changed for simulations. This will enable to quantify performance shortcomings of today’s ocean models (both in accuracy and scalability), allow to adjust model accuracy to forecast uncertainties for different forecast lead times, and help to perform targeted model developments in the future (such as the use of concurrency or improvements for the coupling of fast surface modes and the deep ocean).
The Scientist will study the use of mixed precision in ocean models and identify whether machine learning techniques, and in particular deep neural networks, can be used to emulate specific model components.
The position will be funded via the Horizon2020 Centre of Excellence in Simulation of Weather and Climate in Europe 2 (ESiWACE2)[1]. One of the main goals of ESiWACE2 is to substantially improve efficiency and productivity of numerical weather and climate simulations on high-performance computing platforms by supporting the end-to-end workflow of global Earth system models. The Scientist will contribute to dissemination and training activities of the ESiWACE2 project, work closely together with core staff at ECMWF and collaborate with other projects that are externally funded by the European Commission through its Horizon-2020 programme, for example ESCAPE-2[2], EPiGRAM-HS[3] and EuroEXA[4].
Main duties and key responsibilities
To perform scientific and technical developments within the coupled atmosphere/ocean model at ECMWF to allow for simulations at higher resolution. This includes tests of mixed precision arithmetic in ocean models.
To perform model simulations with ocean models at eddy-resolving resolution and elaborate a framework to test model configurations that use different parameter settings, boundary conditions, resolution and numerical precision to identify and quantify shortcomings and challenges in today’s ocean models and their impact on forecast skill at different forecast lead-times (days to centuries).
To study the ability of deep learning techniques to emulate model components of the Integrated Forecast System to improve computational efficiency.
Personal attributes
Enthusiasm to tackle challenging research questions when working with a complex computer model that is solving an underlying system with non-linear dynamics
Excellent analytical and problem-solving skills with an independent and proactive approach, together with an interest in identifying, investigating and solving technical challenges
Enthusiasm about computers and programming, and willingness to learn new algorithms and tools
Ability to work in a small team and enthusiasm to work towards a common goal
Good interpersonal and communication skills, particularly listening to and respecting the views of others
Qualifications and experience required

Education

A university degree, or equivalent, in a discipline related to computer science,
meteorology, physics, mathematics or engineering is required.

A PhD in a related subject is desirable but not essential.

Experience

Experience in developing complex codes, parallel computing environments and high-performance computing facilities.
Experience working with numerical models in computational fluid dynamics.

Experience working with global atmosphere and/or ocean models would be advantageous.

Experience working in projects and teams governed by tight schedules would
be advantageous.

Experience working with deep-learning and neural networks would be advantageous.

Knowledge and skills (including language)

Good knowledge of at least one high-level programming language such as C++ or Fortran.

Ability to work in a Linux-based environment.

Good understanding of parallel programming (e.g. MPI and OpenMP) would be useful.

A good knowledge of Python would be useful.

Candidates must be able to work effectively in English and interviews will be conducted in English.

A good knowledge of one of the Centre’s other working languages (French or German) would be an advantage.

Other information
Grade remuneration
The successful candidate will be recruited at the A2 grade, according to the scales of the Co-ordinated Organisations and the annual basic salary will be £59,228.40 net of tax. This position is assigned to the employment category STF-PL as defined in the Staff Regulations.
Full details of salary scales and allowances are available on the ECMWF website at www.ecmwf.int/en/about/jobs, including the Centre’s Staff Regulations regarding the terms and conditions of employment.
Starting date: As soon as possible.
Length of contract: Until 31 December 2022.
Location: The position will be based in the Reading area, in Berkshire, United Kingdom.
How to apply
Please apply by completing the online application form available at www.ecmwf.int/en/about/jobs.
To contact the ECMWF Recruitment Team, please email jobs at ecmwf.int.
At ECMWF, we consider an inclusive environment as key for our success. We are dedicated to ensuring a workplace that embraces diversity and provides equal opportunities for all, without distinction as to race, gender, age, marital status, social status, disability, sexual orientation, religion, personality, ethnicity and culture. We value the benefits derived from a diverse workforce and are committed to having staff that reflect the diversity of the countries that are part of our community, in an environment that nurtures equality and inclusion.

Staff are usually recruited from among nationals of the following Member States and Co‑operating States:
Austria, Belgium, Bulgaria, Croatia, Czech Republic, Denmark, Estonia, Finland, former Yugoslav Republic of Macedonia, France, Hungary, Germany, Greece, Iceland, Ireland, Israel, Italy, Latvia, Lithuania, Luxembourg, Montenegro, Morocco, the Netherlands, Norway, Portugal, Romania, Serbia, Slovakia, Slovenia, Spain, Sweden, Switzerland, Turkey and the United Kingdom.
Staff from other countries may be considered in exceptional cases.




________________________________
Julie Palmer
Recruitment and Talent Management Officer
ECMWF | HR Section
e: julie.palmer at ecmwf.int<mailto:julie.palmer at ecmwf.int> t: +44 1189 49 9161

________________________________

[1] www.esiwace.eu

[2] www.hpc-escape.eu

[3] www.epigram-hs.eu

[4] www.euroexa.eu
-------------- next part --------------
An HTML attachment was scrubbed...
URL: <http://mailman.ucar.edu/pipermail/es_jobs_net/attachments/20190307/def6ed93/attachment.html>