16 nov 2020
Data Assimilation Scientist
| Branche | Zie onder |
| Dienstverband | Zie onder |
| Uren | Zie onder |
| Locatie | |
| Opleidingsniveau | Zie onder |
| Organisatie | Met Office |
| Contactpersoon | Zie onder |
Informatie
The Data Assimilation and Ensembles (DAE) section of Weather Science undertakes research and development in observations processing, data assimilation and ensemble forecasting. The
Background information
The Data Assimilation and Ensembles (DAE) section of Weather Science undertakes research and development in observations processing, data assimilation and ensemble forecasting. The work of DAE is focussed on improving the quality of Met Office forecasts, especially of severe weather over the UK.
Objectives of the Ensemble-Variational Data Assimilation Group are research and development of a unified ensemble-variational data-assimilation capability suitable for all Met Office model configurations (global/convective-scale). Specific objectives are a) Research towards the development of next-generation ensemble-variational data-assimilation capabilities, b) Improving the use of ensemble information within the current hybrid 4D-Var/Ensemble Transform Kalman Filter (ETKF) algorithm, and c) Enhancing the initial condition perturbations used by the Met Office Global Regional Ensemble Prediction System (MOGREPS).
The use of ensemble information in data-assimilation has already brought improved forecasts for NWP. Next-generation ensemble-variational data-assimilation methods are being investigated within the group to further improve initial conditions for NWP through the use of ensemble information. The post-holder will be part of a team developing this capability so that it becomes suitable for operational implementation. This will involve conducting research to understand how the new system performs and developing new techniques to improve its performance. It will also involve working with others to further optimize the code for current and future HPC architectures. The post holder will be expected to perform new research and publish results in the peer-reviewed literature.
We welcome applications from people with different levels of experience. We will appoint at the level appropriate to the successful applicant, either at the scientist level or the senior scientist level. Once in post the independence and skill they are expected to deliver will reflect this level. We have distinguished the skills we expect to see at each level in the person specification below. Specific job purpose To deliver scientific and technical improvements to Met Office's ensemble-variational data assimilation capabilities; to enhance the Met Office's reputation; to improve the quality of its products through improvements to the analyses used as initial conditions for NWP.
Specific job responsibilities
Qualifications, skills and abilities required
Essential
Desirable
Application forms and further information
Please mark your request or returned application form: Ensemble Data Assimilation Scientist 002692 R
Please apply with your CV and cover letter by the 'apply' button below.
Please use "Qreer.com" as reference in your application.
Background information
The Data Assimilation and Ensembles (DAE) section of Weather Science undertakes research and development in observations processing, data assimilation and ensemble forecasting. The work of DAE is focussed on improving the quality of Met Office forecasts, especially of severe weather over the UK.
Objectives of the Ensemble-Variational Data Assimilation Group are research and development of a unified ensemble-variational data-assimilation capability suitable for all Met Office model configurations (global/convective-scale). Specific objectives are a) Research towards the development of next-generation ensemble-variational data-assimilation capabilities, b) Improving the use of ensemble information within the current hybrid 4D-Var/Ensemble Transform Kalman Filter (ETKF) algorithm, and c) Enhancing the initial condition perturbations used by the Met Office Global Regional Ensemble Prediction System (MOGREPS).
The use of ensemble information in data-assimilation has already brought improved forecasts for NWP. Next-generation ensemble-variational data-assimilation methods are being investigated within the group to further improve initial conditions for NWP through the use of ensemble information. The post-holder will be part of a team developing this capability so that it becomes suitable for operational implementation. This will involve conducting research to understand how the new system performs and developing new techniques to improve its performance. It will also involve working with others to further optimize the code for current and future HPC architectures. The post holder will be expected to perform new research and publish results in the peer-reviewed literature.
We welcome applications from people with different levels of experience. We will appoint at the level appropriate to the successful applicant, either at the scientist level or the senior scientist level. Once in post the independence and skill they are expected to deliver will reflect this level. We have distinguished the skills we expect to see at each level in the person specification below. Specific job purpose To deliver scientific and technical improvements to Met Office's ensemble-variational data assimilation capabilities; to enhance the Met Office's reputation; to improve the quality of its products through improvements to the analyses used as initial conditions for NWP.
Specific job responsibilities
- To carry out research to improve the quality of forecasts produced by Met Office systems, for the benefit of all customers of NWP.
- To understand the performance of the data assimilation system, using both standard and novel data assimilation diagnostics.
- To work with others on the development of ensemble-variational data-assimilation systems so that they run more efficiently and are able to be used operationally.
- To provide scientific/technical advice to other team members on some work aspects to improve the effectiveness of the team.
- To contribute significantly to the presentation, publication and documentation of work internally and externally in order to maintain our scientific capability and integrity in data-assimilation and thereby promoting our reputation.
Qualifications, skills and abilities required
Essential
- A degree (2:1 or above) in a physical science, mathematics or other related discipline or equivalent experience.
- Scientist: Competence in postgraduate research and development in data assimilation, or a related field, as demonstrated by award of a PhD, or equivalent experience.
Senior Scientist: Extensive experience and proven track record of scientific research. - Good ability to write effective scientific software and to work with large/complex sections of computer code.
- Scientist: Ability to clearly communicate the work of their team to non specialists.
Senior Scientist: Demonstrated ability to communicate their work and to specialists and non specialists and to be able to interact with them in a clear and concise manner with influence and authority. - Scientist: Ability to work effectively both as an independent scientist but also as part of a larger team involving colleagues at the Met Office and international UM partners.
Senior Scientist: Evidence of ability to provide scientific/technical leadership or mentoring to junior staff.
Desirable
- Knowledge of ensemble forecasting and data-assimilation science.
- Knowledge of MPI and OpenMP.
Application forms and further information
Please mark your request or returned application form: Ensemble Data Assimilation Scientist 002692 R
Please apply with your CV and cover letter by the 'apply' button below.
Please use "Qreer.com" as reference in your application.
Omschrijving
The Data Assimilation and Ensembles (DAE) section of Weather Science undertakes research and development in observations processing, data assimilation and ensemble forecasting. The
Background information
The Data Assimilation and Ensembles (DAE) section of Weather Science undertakes research and development in observations processing, data assimilation and ensemble forecasting. The work of DAE is focussed on improving the quality of Met Office forecasts, especially of severe weather over the UK.
Objectives of the Ensemble-Variational Data Assimilation Group are research and development of a unified ensemble-variational data-assimilation capability suitable for all Met Office model configurations (global/convective-scale). Specific objectives are a) Research towards the development of next-generation ensemble-variational data-assimilation capabilities, b) Improving the use of ensemble information within the current hybrid 4D-Var/Ensemble Transform Kalman Filter (ETKF) algorithm, and c) Enhancing the initial condition perturbations used by the Met Office Global Regional Ensemble Prediction System (MOGREPS).
The use of ensemble information in data-assimilation has already brought improved forecasts for NWP. Next-generation ensemble-variational data-assimilation methods are being investigated within the group to further improve initial conditions for NWP through the use of ensemble information. The post-holder will be part of a team developing this capability so that it becomes suitable for operational implementation. This will involve conducting research to understand how the new system performs and developing new techniques to improve its performance. It will also involve working with others to further optimize the code for current and future HPC architectures. The post holder will be expected to perform new research and publish results in the peer-reviewed literature.
We welcome applications from people with different levels of experience. We will appoint at the level appropriate to the successful applicant, either at the scientist level or the senior scientist level. Once in post the independence and skill they are expected to deliver will reflect this level. We have distinguished the skills we expect to see at each level in the person specification below. Specific job purpose To deliver scientific and technical improvements to Met Office's ensemble-variational data assimilation capabilities; to enhance the Met Office's reputation; to improve the quality of its products through improvements to the analyses used as initial conditions for NWP.
Specific job responsibilities
Qualifications, skills and abilities required
Essential
Desirable
Application forms and further information
Please mark your request or returned application form: Ensemble Data Assimilation Scientist 002692 R
Please apply with your CV and cover letter by the 'apply' button below.
Please use "Qreer.com" as reference in your application.
Background information
The Data Assimilation and Ensembles (DAE) section of Weather Science undertakes research and development in observations processing, data assimilation and ensemble forecasting. The work of DAE is focussed on improving the quality of Met Office forecasts, especially of severe weather over the UK.
Objectives of the Ensemble-Variational Data Assimilation Group are research and development of a unified ensemble-variational data-assimilation capability suitable for all Met Office model configurations (global/convective-scale). Specific objectives are a) Research towards the development of next-generation ensemble-variational data-assimilation capabilities, b) Improving the use of ensemble information within the current hybrid 4D-Var/Ensemble Transform Kalman Filter (ETKF) algorithm, and c) Enhancing the initial condition perturbations used by the Met Office Global Regional Ensemble Prediction System (MOGREPS).
The use of ensemble information in data-assimilation has already brought improved forecasts for NWP. Next-generation ensemble-variational data-assimilation methods are being investigated within the group to further improve initial conditions for NWP through the use of ensemble information. The post-holder will be part of a team developing this capability so that it becomes suitable for operational implementation. This will involve conducting research to understand how the new system performs and developing new techniques to improve its performance. It will also involve working with others to further optimize the code for current and future HPC architectures. The post holder will be expected to perform new research and publish results in the peer-reviewed literature.
We welcome applications from people with different levels of experience. We will appoint at the level appropriate to the successful applicant, either at the scientist level or the senior scientist level. Once in post the independence and skill they are expected to deliver will reflect this level. We have distinguished the skills we expect to see at each level in the person specification below. Specific job purpose To deliver scientific and technical improvements to Met Office's ensemble-variational data assimilation capabilities; to enhance the Met Office's reputation; to improve the quality of its products through improvements to the analyses used as initial conditions for NWP.
Specific job responsibilities
- To carry out research to improve the quality of forecasts produced by Met Office systems, for the benefit of all customers of NWP.
- To understand the performance of the data assimilation system, using both standard and novel data assimilation diagnostics.
- To work with others on the development of ensemble-variational data-assimilation systems so that they run more efficiently and are able to be used operationally.
- To provide scientific/technical advice to other team members on some work aspects to improve the effectiveness of the team.
- To contribute significantly to the presentation, publication and documentation of work internally and externally in order to maintain our scientific capability and integrity in data-assimilation and thereby promoting our reputation.
Qualifications, skills and abilities required
Essential
- A degree (2:1 or above) in a physical science, mathematics or other related discipline or equivalent experience.
- Scientist: Competence in postgraduate research and development in data assimilation, or a related field, as demonstrated by award of a PhD, or equivalent experience.
Senior Scientist: Extensive experience and proven track record of scientific research. - Good ability to write effective scientific software and to work with large/complex sections of computer code.
- Scientist: Ability to clearly communicate the work of their team to non specialists.
Senior Scientist: Demonstrated ability to communicate their work and to specialists and non specialists and to be able to interact with them in a clear and concise manner with influence and authority. - Scientist: Ability to work effectively both as an independent scientist but also as part of a larger team involving colleagues at the Met Office and international UM partners.
Senior Scientist: Evidence of ability to provide scientific/technical leadership or mentoring to junior staff.
Desirable
- Knowledge of ensemble forecasting and data-assimilation science.
- Knowledge of MPI and OpenMP.
Application forms and further information
Please mark your request or returned application form: Ensemble Data Assimilation Scientist 002692 R
Please apply with your CV and cover letter by the 'apply' button below.
Please use "Qreer.com" as reference in your application.
