[ES_JOBS_NET] Job Vacancy at ECMWF for: Scientist - Ocean Assimilation, Closing date: 8 February 2019

[Julie Palmer]

Dear Mailing list,

I am sharing the following job vacancy for:


Scientist – Ocean Assimilation

Position information



Vacancy No.: VN18-44


Department: Research


Grade: A2


Section: Earth System Assimilation


Job Ref. No.: STF-C/18-44


Reports to: Team Leader Coupled Data Assimilation


Publication Date: 14 December 2018


Closing Date: 24 January 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. This data is fully available to the national meteorological services in the Member States. The Centre also offers a catalogue of forecast data that can be purchased by businesses worldwide and other commercial customers. The supercomputer facility (and associated data archive) at ECMWF is one of the largest of its type in Europe and Member States can use 25% of its capacity for their own purposes.



For details, see www.ecmwf.int

ECMWF uses its high-performance computing (HPC) facility to produce a time-critical twice-daily global numerical weather forecast. The operational forecasting system and research & development are currently run on two Cray XC-40 clusters totalling over 250,000 Intel Broadwell compute cores each. Given the expected need for increasing the Earth system model resolution and complexity, enhanced parallelism in work flows and computer code are required, as may be the exploitation of emerging hardware architectures such as low-power multicore CPUs combined with FPGAs.

1.          Summary of the role



In 2016, ECMWF committed to a new strategy up to 2025. The strategy aims to improve medium-range, extended range and seasonal forecasts by better representing processes taking place on a range of timescales in multiple Earth System components. This requires effort to raise the scientific and technical capability for non-atmospheric components of the Earth System assimilation and modelling. One aspect of this is increased emphasis to the ocean. This post will develop ocean data assimilation, with some aspects developed in-house and others in partnership with external agencies. The job holder will also support activities to integrate the ocean component fully into the Object Orientated Prediction System (OOPS), which will require support to aspects of the ocean model, in collaboration with the Earth System Modelling and Integrated Forecast Systems Sections within the Research Department. This will support ECMWF’s goal of a coupled ocean-atmosphere data assimilation system.



We are looking to recruit a scientist who will work with us on the scientific and technical development of the ocean data assimilation, using modern code architectures, and with the longer-term goal of a coupled ocean-atmosphere data assimilation system capable of ingesting raw Level-1 observations from satellites and in situ measurements to create a balanced initial state both in the ocean itself, and between ocean and atmosphere. The focus will be on the ocean component of the data assimilation. This position will require both state-of-the-art scientific research but also a strong technical capability, as well as work needed to implement changes, and subsequently provide expert support, to the operational system.



The position sits within the Earth System Assimilation Section at ECMWF and will report to the Coupled Data Assimilation Team Leader.

Main duties and key responsibilities

·      Integrating ocean DA developments targeting an ECMWF SST analysis

·      Contributing to the scientific and technical development, as well as monitoring of the ocean data assimilation, within the Object Orientated Prediction System (OOPS)

·      Contributing to the configuration of operational ocean reanalyses and real-time analyses, including updated observational data sets and latest methodology

·      Supporting other teams in the Research Department in related technical developments

·      Integrating developments from external partners, both through the NEMOVAR consortium and more generally

Personal attributes

·      Excellent analytical and problem-solving skills with a proactive approach, together with an interest in identifying, investigating and solving technical challenges

·      Enthusiasm and willingness to learn new algorithms and tools

·      Ability to work in a small team

·      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, oceanography, physics, mathematics or engineering is required.

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



Evidence of ability to have undertaken independent research in a related area, equivalent to that demonstrated by a PhD, is essential.


Experience


Experience in practical application of data assimilation methods is essential.



Familiarity with ocean data assimilation and observations is highly desirable.



Familiarity with direct assimilation of observations in variational or similar assimilation framework is highly desirable.



Familiarity with working on complex codes.



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


Knowledge and skills (including language)


Good knowledge of a high-level programming language such as C++.



Fortran is essential.



Knowledge of both object-orientated programming and Python would be useful.



Ability to work in a Linux-based environment.



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



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-C 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: Four years, with the possibility of a further contract.

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

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