52,799 - 56,738
A Civil Service Pension with an employer contribution of 28.97%
GBP
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Job grade
Grade 7###
Contract type
Permanent###
Type of role
Science###
Working pattern
Full-time###
Number of jobs available
1
Contents
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Location
About the job
Benefits
Things you need to know
Apply and further information
Location
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Exeter, South West England, EX1 3PB
About the job
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Job summary
We're looking for an exceptional
Science Manager: Intra-model Machine Learning
to help us make a difference to our planet.
As our Science Manager: Intra-model Machine Learning, the job may be suitable for hybrid working, which is where an employee works part of the week in the office and part of the week from home. This is a voluntary, non-contractual arrangement and the location advertised will be your contractual place of work.
Our opportunity is full time, 37 hours per week, but we would also consider applicants wishing to work a minimum of 30 hours per week. Our people are at the heart of what we do, and we'll do our best to agree a working pattern that works for everyone.
World changing work
From science to technology, from meteorology to management, and from planning to communication, our expertise helps us stand out as the authority on weather accuracy and climate prediction. We help individuals, industries and government to make better decisions to stay safe and thrive. This is the Met Office. This is who we are.
We're a force for good - focusing on our environmental and social impact
We're experts by nature - always learning and developing to do things better
We live and breathe it - putting our purpose at the heart of decision-making
We're better together - understanding partnerships and inclusivity make us greater
We keep evolving - pushing boundaries to make tomorrow better for our customers
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Job description
Your world of expertise
You will lead a team carrying out scientific research to couple machine-learnt elements into the physical models used for weather prediction and climate projection. By combining atmospheric science knowledge with machine learning and stochastic physics techniques you will deliver improvements to the simulations used to help keep people safe.
Your key duties:
To work as part of the Atmospheric Processes and Parametrization management team.
To contribute to setting the strategic direction of the Research and Development programme for parametrization emulation and development against a landscape of rapid developments in machine learning and modelling capabilities.
To creatively and positively lead and develop a team of research scientists and scientific software engineers.
To carry out innovative scientific research in the development and use of intra-model machine learning and stochastic physics to enhance the Met Office's modelling capability and international reputation and for the benefit of our customers.
To lead and stimulate scientific and software collaborations across the Met Office, the UK and internationally with relevant experts, identifying and pursuing opportunities to facilitate the group's ongoing research and amplify the impact of their work.
To lead, coordinate and ensure the pull-through of research and software developments into atmospheric model configurations for use operationally.
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Person specification
Essential Criteria, skills and experience:
Evidence of research experience in mathematical, physical or environmental science (e.g. PhD + several years' postdoc, or demonstration of equivalent experience) and an ability to lead the successful publication of scientific work (We're Experts by Nature)
Demonstrable experience of project management, leading to pull-through of scientific and technical developments, demonstrating sustained scientific integrity and effective software quality assurance (We're Better Together)
Proven ability to learn new skills and evidence of interest in, and technical understanding of, machine learning and stochastic physics, and their uses in improving atmospheric modelling capabilities (We Keep Evolving)
An interest in people management and clear potential to manage and motivate diverse and inclusive teams (We're Better Together:)
Excellent understanding of atmospheric science and the role of parametrizations in improving global and regional, and weather and climate predictions (We Live and Breathe It).
Evidence of excellent communication skills leading to fruitful collaborations (written, oral, presentation and listening).
Proven ability to make effective use of mentoring and development of others, to build upon own delivery and achieve more through teamwork (We're Better Together).
Benefits
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Alongside your salary of 52,799, Met Office contributes 15,295 towards you being a member of the Civil Service Defined Benefit Pension scheme. Find out what benefits a Civil Service Pension provides.
Why join us
Our work is life-changing, often life-saving and always life-enhancing. The Met Office is Great Place to Work UK certified. We are also featured on their 'Best Workplaces in Tech' 2023 and 2024 lists, as well as their '54 Best Workplaces for Women' 2023 list.
As our Science Manager: Intra-model Machine Learning, your total reward package will be up to 73,518 annually, which includes:
52,799 base pay
An outstanding Civil Service pension, with an average employer contribution of 28.97%
Annual Leave starting at 27.5 days (plus Bank Holidays) rising to 32.5 days (plus Bank Holidays) after 5 years and option to buy or sell up to 5 days per year of annual leave
Things you need to know
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Selection process details
How to apply
If you share our values, we'd love to hear from you! Click apply to begin your application. Please complete your career history and provide evidence against each of the essential criteria in the supporting statement questionnaire. We recommend candidates use the CARL method (Context, Action, Result and Learning) for presenting evidence of experience and skills.
Closing date 31/10/2025 at 23:59 with first stage interviews commencing from 17/11/2025. You will hear from us once the closing date has passed.
Using AI in your application
We welcome applications that use AI tools for support in drafting or refining, as long as they accurately reflect your own skills and experience. All hiring decisions at the Met Office are made by people, not AI. For more details, visit our approach to recruitment.
How we can help
If you have any questions or would like to discuss this opportunity further, please contact us at careers@metoffice.gov.uk.
If you're considering applying and need support to do so, please get in touch. You can request adjustments either within your application or by contacting us. Should you be offered an interview, please be aware there may be a selection exercise which could include a presentation, written test or a scenario-based activity. You can select in your application to be considered under the Disability Confident Scheme. To be invited to interview/assessment under this scheme, your application must meet the essential criteria for the role.
We understand that great minds don't always think alike and as an equal opportunities employer we welcome applications from those with all protected characteristics. We recruit on merit, fairness, and open competition in line with the Civil Service Code.
We can only accept applications from those eligible to live and work in the UK - please refer to GOV.UK for information. We require Security clearance, for which you need to have resided in the UK for at least 3 of the last 5 years to be eligible, 2 of these years must be immediately preceding the point of your application. You will need to achieve full security clearance within your first 6 months with us.
Feedback will only be provided if you attend an interview or assessment.###
Security
Successful candidates must meet the security requirements before they can be appointed. The level of security needed is security check .
See our vetting charter .
People working with government assets must complete baseline personnel security standard (opens in new window) checks.###
Medical
Successful candidates will be expected to have a medical.###
Nationality requirements
This job is broadly open to the following groups:
UK nationals
nationals of the Republic of Ireland
nationals of Commonwealth countries who have the right to work in the UK
nationals of the EU, Switzerland, Norway, Iceland or Liechtenstein and family members of those nationalities with settled or pre-settled status under the European Union Settlement Scheme (EUSS)
nationals of the EU, Switzerland, Norway, Iceland or Liechtenstein and family members of those nationalities who have made a valid application for settled or pre-settled status under the European Union Settlement Scheme (EUSS)
individuals with limited leave to remain or indefinite leave to remain who were eligible to apply for EUSS on or before 31 December 2020
Turkish nationals, and certain family members of Turkish nationals, who have accrued the right to work in the Civil Service
Further information on nationality requirements
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Working for the Civil Service
The Civil Service Code sets out the standards of behaviour expected of civil servants.
We recruit by merit on the basis of fair and open competition, as outlined in the Civil Service Commission's recruitment principles .
The Civil Service embraces diversity and promotes equal opportunities. As such, we run a Disability Confident Scheme (DCS) for candidates with disabilities who meet the minimum selection criteria.###
Diversity and Inclusion
The Civil Service is committed to attract, retain and invest in talent wherever it is found. To learn more please see the Civil Service People Plan and the Civil Service Diversity and Inclusion Strategy .
Apply and further information
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The Civil Service welcomes applications from people who have recently left prison or have an unspent conviction. Read more about prison leaver recruitment (opens in new window).
Once this job has closed, the job advert will no longer be available. You may want to save a copy for your records.###
Contact point for applicants
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Job contact :
Name : Resourcing Team
Email : careers@metoffice.gov.uk
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Recruitment team
* Email : careers@metoffice.gov.uk
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