Opportunities
The Strategic Priorities Fund programmes will bring together a broad range of research disciplines to drive an increase in high quality multi- and interdisciplinary research and innovation.
We will be allocating funding for the Clean Air, UK Climate Resilience and ExCALIBUR programmes through open competition.
There are no current open calls for the Clean Air or UK Climate Resilience programmes. Details on current ExCALIBUR opportunities can be found below.
ExCALIBUR funding opportunities
Read about the ExCALIBUR programme aims and cross-cutting theme calls
SPF ExCALIBUR: EX20-6 I/O & Storage
SPF ExCALIBUR EX20- 7: Data Workflow
SPF ExCALIBUR: EX20-8 Exposing Parallelism: Parallel in Time
SPF ExCALIBUR: EX20-9 Exposing Parallelism: Task Parallelism
SPF ExCALIBUR: EX20-10 Machine learning: optimising numerical methods and augmenting physically based applications
Expressions of Interest for: Met Office SPF ExCALIBUR: EX20-6 I/O & Storage
Call Reference: DN517485
Met Office tendering on behalf of BEIS.
To register your interest, see notes at the end of this page. Registering interest requires no proposal detail at this stage and carries no obligation to bid.
Please note that this Expression of Interest is open to UK operating and registered organisations.
Grant Funds for the period 01/06/2021 - 31/05/2024
Call for competition to cover the following call:
| Title | Amount | fEC @100% | fEC @ 80% |
|---|---|---|---|
| EX20-6: I/O & storage | £750,000 | £750,000 | £600,000 |
| FEC | Total Amount | 2021/22 | 2022/23 | 2023/24 | 2024/25 |
|---|---|---|---|---|---|
| 100% | £750k | £190k | £250k | £250k | £60k |
| 80% | £600k | £152k | £200k | £200k | £48k |
Key Dates
|
Estimated Publish of Call: (Start of bidding period |
w/c 18 January 2021 A notification email will be sent to parties who have formally registered their interest by way of clicking on the ‘Register Interest’ button displayed below the opportunity on the ProContract portal |
|---|---|
| Estimated Bidding Period: | 7 weeks |
| Estimated Award of Call: | 07/05/2021 |
| Estimated Delivery Period: | 01/06/2021 – 31/05/2024 |
Background of Requirement
Successful Exascale simulations will require optimal flow of exabytes of data from long-term storage units, where the data are distributed in some way, through a multitude of increasingly smaller but faster storage devices until appropriately small packages of data (distributed in a completely different way to how they started out) reach the relevant processing entity which will have orders of magnitude smaller memory than the initial data set. Some of that data will need to be shared with other processing entities. Then at some point all those packages of data will need to journey back through the deep memory hierarchy to end up back in the long-term storage units. This aspect is amplified when ensembles of simulations are used for uncertainty quantification. This data flow can be broadly captured by the term I/O.
The optimisation of I/O through all the different storage media is a huge challenge but one that must be addressed to make Exascale simulations viable. However, that optimisation is likely to vary depending on the precise details of each simulation and what storage is available, which might be a function of time (e.g. where resources are shared with other applications). It will also vary, potentially radically, when new storage media are added to a system or when the same application is run on a different machine. It is unreasonable to expect a user, no matter how expert that user is, to know how to optimally configure each simulation nor should they need to know how the data was written in order to be able to effectively interact with it.
This activity will explore how this problem can be addressed, develop prototype implementations of potential solutions, demonstrate their effectiveness in a context that is of direct relevance to the use cases, and propose a roadmap for how use cases can adopt such solutions for practical large-scale applications. As an example, a potential solution might be a separation-of-concerns approach, implemented via some form of middleware between tape and object stores, that separates the domain scientist from the detail of the storage media and allows either automatic or bespoke optimisations to be applied dependent on the target system architectures (akin to the separation-of-concerns approach being developed for alternative parallelisation paradigms).
The output of the activity should be applicable to at least two out of: the Weather & Climate Prediction Use Case; the Fusion Modelling Use Case; and any collection of the Design & Development Working Group Use Cases. Code should be developed for one of these and a report prepared on the applicability to one or more of the others.
Knowledge Exchange is a vital component of achieving the objectives of the ExCALIBUR programme; it will ensure integration across the programme activities where researchers are developing software and algorithms in preparation for future Exascale systems. Additionally, connections are required with potential beneficiaries in academia, Public Sector Research Establishments (PSREs) and industry to contribute to these designs and the dissemination of outcomes. Therefore, proposals must include a named Co-investigator or Research Co-investigator who will have the role of a Knowledge Exchange Co-ordinator to lead these endeavours.
Expectations for this role include, but are not limited to:
• Identify opportunities for Knowledge Exchange within their project/grant, with other ExCALIBUR programme projects/grants, and with other relevant national & international projects.
• Identify opportunities for Knowledge Exchange to develop and maintain a two-way flow of engagement and dissemination with industry and relevant national & international research communities.
• Develop a plan to increase the awareness of the proposed activity and the ExCALIBUR programme.
• Collaborate with other ExCALIBUR Knowledge Exchange Co-ordinators as a network to deliver the programme’s knowledge dissemination strategy.
How to Apply:
The above Expression of Interest is advertised on the Met Office ProContract e-Tendering portal called ProContract. To access and register your interest you will need to log onto the ProContract portal via this link: tenders.metoffice.gov.uk
You may need to search for the Call reference: DN517485
Expressions of Interest for: Met Office SPF ExCALIBUR EX20- 7: Data Workflow
Call Reference: DN517488
Met Office tendering on behalf of BEIS.
To register your interest, see notes at the end of this page. Registering interest requires no proposal detail at this stage and carries no obligation to bid.
Please note that this Expression of Interest is open to UK operating and registered organisations.
Grant Funds for the period 01/06/2021 to 31/05/2024
Call for competition to cover the following call:
| Title | Amount | fEC @100% | fEC @ 80% |
|---|---|---|---|
| EX20-7: Data Workflow | £750,000 | £750,000 | £600,000 |
| FEC | Total Amount | 2021/22 | 2022/23 | 2023/24 | 2024/25 |
|---|---|---|---|---|---|
| 100% | £750k | £190k | £250k | £250k | £60k |
| 80% | £600k | £152k | £200k | £200k | £48k |
Key Dates
| Estimated Publish of Call: (Start of bidding period). |
w/c 18th January 2021
|
|---|---|
| Estimated Bidding Period: | 7 weeks |
| Estimated Award of Call: | 07/05/2021 |
| Estimated Delivery Period: | 01/06/2021 – 31/05/2024 |
Background of Requirement
Successful Exascale simulations will require optimal flow of exabytes of data from long-term storage units, where the data are distributed in some way, through a multitude of increasingly smaller but faster storage devices until appropriately small packages of data (distributed in a completely different way to how they started out) reach the relevant processing entity which will have orders of magnitude smaller memory than the initial data set. Some of that data will need to be shared with other processing entities. Then at some point all those packages of data will need to journey back through the deep memory hierarchy to end up back in the long-term storage units. This aspect is amplified when ensembles of simulations are used for uncertainty quantification. This data flow can be broadly captured by the term I/O.
The optimisation of I/O through all the different storage media is a huge challenge but one that must be addressed to make Exascale simulations viable. One approach to optimising I/O is to reduce the need to move the data around in the first place. This can be achieved by moving the computation to the data. This might be achieved by developing methods for applying standard operations to data in their long-term storage format or by applying those operations (and probably a much larger range of operations) within the applications that manage the data movement, the I/O servers, for example XIOS.
This activity will explore how moving-(certain aspects of)-computation-to-the-data can be best achieved within the chosen use cases, develop prototype implementations of potential approaches, demonstrate their effectiveness for the target use cases, and then explore how such approaches can be generalised to a much wider range of use cases. This generalisation will likely involve aspects of standardisation, for example involving HDF/NetCDF, and/or abstraction. It is anticipated that the greatest improvement will come from exploring aspects of ensemble applications since this is where, for a given problem size, the I/O problems are most acute. It is also recognised that aspects of this work might depend on the workflows having, or being redesigned to have, specific characteristics to enable the effectiveness of this work.
The output of the activity should be applicable to at least two out of: the Weather & Climate Prediction Use Case; the Fusion Modelling Use Case; and any collection of the Design & Development Working Group Use Cases. Code should be developed for one of these and a report prepared on the applicability to one or more of the others.
Knowledge Exchange is a vital component of achieving the objectives of the ExCALIBUR programme; it will ensure integration across the programme activities where researchers are developing software and algorithms in preparation for future Exascale systems. Additionally, connections are required with potential beneficiaries in academia, Public Sector Research Establishments (PSREs) and industry to contribute to these designs and the dissemination of outcomes. Therefore, proposals must include a named Co-investigator or Research Co-investigator who will have the role of a Knowledge Exchange Co-ordinator to lead these endeavours. Expectations for this role include, but are not limited to:
• Identify opportunities for Knowledge Exchange within their project/grant, with other ExCALIBUR programme projects/grants, and with other relevant national & international projects.
• Identify opportunities for Knowledge Exchange to develop and maintain a two-way flow of engagement and dissemination with industry and relevant national & international research communities.
• Develop a plan to increase the awareness of the proposed activity and the ExCALIBUR programme.
• Collaborate with other ExCALIBUR Knowledge Exchange Co-ordinators as a network to deliver the programme’s knowledge dissemination strategy.
How to Apply:
The above Expression of Interest is advertised on the Met Office ProContract e-Tendering portal called ProContract. To access and register your interest you will need to log onto the ProContract portal via this link: tenders.metoffice.gov.uk
You may need to search for the Call reference: DN517488
You will need to register your company (if you have not already done so) and register your interest against the opportunity before you are able to access the tender documents.
If you require guidance or ‘how to’ instructions – see the supplier manuals on the right-hand side of the supplier home page.
Online Discussions between Bidders and the Met Office:
There is a Discussions function on ProContract which shall be used to provide all further information regarding this opportunity including any changes to time scales, scope or clarifications. This function must be used by bidders to submit all clarification questions.
Expressions of Interest for: Met Office SPF ExCALIBUR: EX20-8 Exposing Parallelism: Parallel in Time
Call Reference: DN517492
Met Office tendering on behalf of BEIS.
To register your interest, see notes at the end of this page. Registering interest requires no proposal detail at this stage and carries no obligation to bid.
Please note that this Expression of Interest is open to UK operating and registered organisations.
Grant Funds for the period: 01/06/2021 – 31/05/2024
Call for competition to cover the following call:
| Title | Amount | fEC @100% | fEC @ 80% |
|---|---|---|---|
| EX20-8 Exposing Parallelism: Parallel-in-Time | £1,200,000 | £1,200,000 | £960,000 |
| FEC | Total Amount | 2021/22 | 2022/23 | 2023/24 | 2024/25 |
|---|---|---|---|---|---|
| 100% | £1,200,000 | £310k | £400k | £400k | £90k |
| 80% | £960,000 | £248k | £320k | £320k | £72k |
| Estimated Publish of Call: (Start of bidding period). |
w/c 18th January 2021
|
|---|---|
| Estimated Bidding Period: | 7 weeks |
| Estimated Award of Call: | 07/05/2021 |
| Estimated Delivery Period: | 01/06/2021 – 31/05/2024 |
Background of Requirement:
Exascale machines will achieve their speed by providing orders of magnitude more processing entities than even current petascale machines have. Therefore, the ability of a code to exploit such machines relies on that code being able to exercise as many as possible of those processing entities concurrently. For petascale machines such parallelism has been principally achieved via decomposing in the spatial domain. Although this axis of decomposition can be further increased to expose further parallelism, the extent to which this is practical is limited for many of the ExCALIBUR use cases. It is therefore essential that alternative axes of parallelism are explored, implemented, and exploited.
One such axis is that of time, i.e. to parallelise in time, as well as in space. This approach has a long history, but a recent revival is showing potential for practical, large-scale applications. A further exciting development is the potential to use Artificial Intelligence/Machine Learning techniques as elements of parallel-in-time methods. Additionally, there is a small but growing, emerging community within the UK of groups working on aspects of parallel-in-time methods as well as similar international efforts. However, challenges remain to be addressed. For example, how effective can parallelisation-in-time be in the presence of a suite of physical parametrisations that are coupled to the core fluid dynamical model? How is the convergence of the scheme, a critical element in its success, affected by such processes, some of which fundamentally change the nature of the partial differential equations being solved, e.g. from hyperbolic to parabolic? How can existing code bases be adapted to apply parallel-in-time methods? Which method is the most appropriate to a given use case?
It is the aim of this activity to capitalise on recent algorithmic developments and the benefits of the existing UK community, as well as the international community, to provide a roadmap and associated infrastructure for the realisation of the benefit of parallel-in-time methods for large-scale, practical applications targeted at future HPCs. The anticipated infrastructure can be viewed as a bridge or a pipeline incorporating all aspects from the mathematical development and analysis of parallel-in-time algorithms, through the development of a standard test suite, through prototyping and testing of various methods in an appropriate modelling framework, to code that is suitable for the target large-scale use-case applications.
The activity is focused on continuum mechanics such as geophysics and astrophysics.
The activity will collate and/or develop a standard set of test cases designed to challenge the approaches to parallel-in-time in as close-to-real way as possible so that the practical pros and cons of different approaches can be ascertained at the earliest stage of development possible. At least one of these should include some representation of a coupled system (e.g. inclusion of a representative parametrisation scheme) and at least some of the test cases should be sufficiently complex that the performance of a scheme on those test cases is likely to broadly reflect their eventual performance in large-scale use cases.
The activity will build an environment that allows the rapid prototyping of a variety of methods and benchmarking of those test cases. Although it is not anticipated that this activity will go as far as demonstrating practical implementation in a large-scale use-case application, the environment that it delivers should be explicitly designed with a view to enabling the target use-case communities to achieve such a transition through to their large-scale operation. That is, the environment should be such that the use-case communities can use its principles as a way (a roadmap) of preparing use-case codes for implementation of parallel-in-time algorithms.
It is anticipated that there could be scope to include as part of the activity exploration of any novel approaches in this area that might be of benefit to the use-case communities.
The output of the activity should be applicable to at least two out of: the Weather & Climate Prediction Use Case; the Fusion Modelling Use Case; and any collection of the Design & Development Working Group Use Cases. Code should be developed for one of these and a report prepared on the applicability to one or more of the others.
Knowledge Exchange is a vital component of achieving the objectives of the ExCALIBUR programme; it will ensure integration across the programme activities where researchers are developing software and algorithms in preparation for future Exascale systems. Additionally, connections are required with potential beneficiaries in academia, Public Sector Research Establishments (PSREs) and industry to contribute to these designs and the dissemination of outcomes. Therefore, proposals must include a named Co-investigator or Research Co-investigator who will have the role of a Knowledge Exchange Co-ordinator to lead these endeavours.
Expectations for this role include, but are not limited to:
• Identify opportunities for Knowledge Exchange within their project/grant, with other ExCALIBUR programme projects/grants, and with other relevant national & international projects.
• Identify opportunities for Knowledge Exchange to develop and maintain a two-way flow of engagement and dissemination with industry and relevant national & international research communities.
• Develop a plan to increase the awareness of the proposed activity and the ExCALIBUR programme.
• Collaborate with other ExCALIBUR Knowledge Exchange Co-ordinators as a network to deliver the programme’s knowledge dissemination strategy.
How to Apply:
The above Expression of Interest is advertised on the Met Office ProContract e-Tendering portal called ProContract. To access and register your interest you will need to log onto the ProContract portal via this link: tenders.metoffice.gov.uk
You may need to search for the Call reference: DN517492
You will need to register your company (if you have not already done so) and register your interest against the opportunity before you are able to access the tender documents.
If you require guidance or ‘how to’ instructions – see the supplier manuals on the right-hand side of the supplier home page.
Online Discussions between Bidders and the Met Office:
There is a Discussions function on ProContract which shall be used to provide all further information regarding this opportunity including any changes to time scales, scope or clarifications. This function must be used by bidders to submit all clarification questions.
Expressions of Interest for: Met Office SPF ExCALIBUR: EX20-9 Exposing Parallelism: Task Parallelism
Call Reference: DN517496
Met Office tendering on behalf of BEIS.
To register your interest, see notes at the end of this page. Registering interest requires no proposal detail at this stage and carries no obligation to bid.
Please note that this Expression of Interest is open to UK operating and registered organisations.
Grant Funds for the period: 01/06/2021 – 31/05/2024
Call for competition to cover the following call:
| Title | Amount | fEC @100% | fEC @ 80% |
|---|---|---|---|
|
EX20-9 Exposing Parallelism: Task Parallelism |
£450,000 | £450,000 | £360,000 |
| FEC | Total Amount | 2021/22 | 2022/23 | 2023/24 | 2024/25 |
|---|---|---|---|---|---|
| 100% | £450k | £120k | £150k | £150k | £30k |
| 80% | £360k | £96k | £120k | £120k | £24k |
Key Dates
| Estimated Publish of Call: (Start of bidding period). |
w/c 18th January 2021
|
|---|---|
| Estimated Bidding Period: | 7 weeks |
| Estimated Award of Call: | 07/05/2021 |
| Estimated Delivery Period: | 01/06/2021 – 31/05/2024 |
Background to requirement:
Exascale machines will achieve their speed by providing orders of magnitude more processing entities than even current petascale machines have. Therefore, the ability of a code to exploit such machines relies on that code being able to exercise as many as possible of those processing entities concurrently. For petascale machines such parallelism has been principally achieved via decomposing in the spatial domain. Although this axis of decomposition can be further increased to expose further parallelism, the extent to which this is practical is limited for many of the ExCALIBUR use cases. It is therefore essential that alternative axes of parallelism are explored, implemented, and exploited.
One such axis is that of task parallelism, i.e. the identification and separation of a process into tasks that, at least for a certain period, can be executed independently of each other. Typically, this approach to parallelism has only been applied at a very coarse level. An example is the coupling together of an ocean model and atmosphere model. This is often done in a way that allows each model to execute on its own, independent set of processing units. However, it is likely that the path to Exascale will require the exposure and exploitation of much finer task parallelism. An example might be to exploit the numerically explicit nature of some physical parametrisations to execute each scheme in parallel on its own, independent set of processing units within the same model. For some ExCALIBUR use cases this has been applied with some success. For others the approach has not been explored at all. This might be due to the particular science domain or how the algorithms have been designed and/or implemented. If the potential for greater task-based parallelism exists for a particular use case, then how should the algorithms be redesigned? Is it worth the effort? How do the domain specialists know?
This activity will investigate and review what the potential for practical application of task-based parallelism to various use cases is and explore how successful approaches might be generically applied. For example, if it is possible to abstract the execution of a task graph from the domain specific science then it might be possible to develop and implement a generic task-graph execution engine. It will additionally investigate, and develop prototype implementations of, methods for abstracting aspects of task-based parallelism that could be interfaced to generic engines or to relevant domain specific languages. If successful, such an approach might allow for the automation of task-parallelism at the algorithmic level.
The output of the activity should be applicable to at least two out of: the Weather & Climate Prediction Use Case; the Fusion Modelling Use Case; and any collection of the Design & Development Working Group Use Cases. Code should be developed for one of these and a report prepared on the applicability to one or more of the others.
Knowledge Exchange is a vital component of achieving the objectives of the ExCALIBUR programme; it will ensure integration across the programme activities where researchers are developing software and algorithms in preparation for future Exascale systems. Additionally, connections are required with potential beneficiaries in academia, Public Sector Research Establishments (PSREs) and industry to contribute to these designs and the dissemination of outcomes. Therefore, proposals must include a named Co-investigator or Research Co-investigator who will have the role of a Knowledge Exchange Co-ordinator to lead these endeavours. Expectations for this role include, but are not limited to:
• Identify opportunities for Knowledge Exchange within their project/grant, with other ExCALIBUR programme projects/grants, and with other relevant national & international projects.
• Identify opportunities for Knowledge Exchange to develop and maintain a two-way flow of engagement and dissemination with industry and relevant national & international research communities.
• Develop a plan to increase the awareness of the proposed activity and the ExCALIBUR programme.
• Collaborate with other ExCALIBUR Knowledge Exchange Co-ordinators as a network to deliver the programme’s knowledge dissemination strategy.
How to Apply:
The above Expression of Interest is advertised on the Met Office ProContract e-Tendering portal called ProContract. To access and register your interest you will need to log onto the ProContract portal via this link: tenders.metoffice.gov.uk
You may need to search for the Call reference: DN517496
You will need to register your company (if you have not already done so) and register your interest against the opportunity before you are able to access the tender documents.
If you require guidance or ‘how to’ instructions – see the supplier manuals on the right-hand side of the supplier home page.
Online Discussions between Bidders and the Met Office:
There is a Discussions function on ProContract which shall be used to provide all further information regarding this opportunity including any changes to time scales, scope or clarifications. This function must be used by bidders to submit all clarification questions.
Expressions of Interest for: Met Office SPF ExCALIBUR: EX20-10 Machine learning: optimising numerical methods and augmenting physically based applications
Call Reference: DN517499
Met Office tendering on behalf of BEIS.
To register your interest, see notes at the end of this page. Registering interest requires no proposal detail at this stage and carries no obligation to bid.
Please note that this Expression of Interest is open to UK operating and registered organisations.
Grant Funds for the period: 01/06/2021 – 31/05/2024
Call for competition to cover the following call:
| Title | Amount | fEC @100% | fEC @ 80% |
|---|---|---|---|
| EX20-10 Machine learning: optimising numerical methods and augmenting physically based applications | £750,000 | £750,000 | £600,000 |
| FEC | Total Amount | 2021/22 | 2022/23 | 2023/24 | 2024/25 |
|---|---|---|---|---|---|
| 100% | £750k | £190k | £250k | £250k | £60k |
| 80% | £600k | £152k | £200k | £200k | £48k |
Key Dates
|
Estimated Publish of Call: |
w/c 18th January 2021 |
|---|---|
| Estimated Bidding Period: | 7 weeks |
| Estimated Award of Call: | 07/05/2021 |
| Estimated Delivery Period: | 01/06/2021 – 31/05/2024 |
Background to requirement:
Machine learning (ML) offers a radical approach to the efficient use of computational resource. Traditionally the focus of its application has been on replacing existing algorithms with machine learnt algorithms. However, this raises concern about the general applicability of such algorithms when they are applied beyond the scope of the data on which they were trained. There has, therefore, been recent interest and developments in fusing machine learning with traditional algorithms. This has included the use of ML for the optimisation of traditional numerical methods such as preconditioners and the choice of optimal stencils, as well as the use of ML for speeding up aspects of physical parametrisations.
However, there is a large zoo of ML tools available, written in various languages. There is similarly a wide range of use cases each with their own code structure. This presents a hurdle for domain scientists to investigate the adoption of ML approaches to their problems. Hence, for the UK’s ExCALIBUR community to be able to efficiently exploit the benefits of ML there is a need for a standardised approach for coupling ML with simulation codes which will permit the training of ML algorithms in situ with the simulation codes. This might be via the development of an interface or it might be the development of a generic library or libraries. As an example, a python-based interface might be a good starting point, but the principles of the structure of the interface should be more generally applicable to other languages either directly, via alternative plug-ins or via an alternative approach such as exploiting the Intermediate Representation approach being adopted by domain specific languages. Whatever approach is proposed it needs to be targeted at supercomputer applications with use on future supercomputer architectures in mind.
This activity will propose a standardised approach, either via libraries or interfaces, to the fusion of a range of ML tools and simulation codes allowing training of the ML algorithms in situ with relevant aspects of the simulation codes of the use cases. The activity will deliver and demonstrate the practical application of the proposal in the context of a supercomputer-based application relevant to the use cases. The approach will be as general as practically possible, and it has to be maintainable and extendable as new ML approaches become available. In particular, if it is based around a specific language the activity will develop a roadmap for how the approach could be extended to other languages, for example by use of plug-ins or via intermediate representations.
The output of the activity should be applicable to at least two out of: the Weather & Climate Prediction Use Case; the Fusion Modelling Use Case; and any collection of the Design & Development Working Group Use Cases. Code should be developed for one of these and a report prepared on the applicability to one or more of the others.
Knowledge Exchange is a vital component of achieving the objectives of the ExCALIBUR programme; it will ensure integration across the programme activities where researchers are developing software and algorithms in preparation for future Exascale systems. Additionally, connections are required with potential beneficiaries in academia, Public Sector Research Establishments (PSREs) and industry to contribute to these designs and the dissemination of outcomes. Therefore, proposals must include a named Co-investigator or Research Co-investigator who will have the role of a Knowledge Exchange Co-ordinator to lead these endeavours. Expectations for this role include, but are not limited to:
• Identify opportunities for Knowledge Exchange within their project/grant, with other ExCALIBUR programme projects/grants, and with other relevant national & international projects.
• Identify opportunities for Knowledge Exchange to develop and maintain a two-way flow of engagement and dissemination with industry and relevant national & international research communities.
• Develop a plan to increase the awareness of the proposed activity and the ExCALIBUR programme.
• Collaborate with other ExCALIBUR Knowledge Exchange Co-ordinators as a network to deliver the programme’s knowledge dissemination strategy.
How to Apply:
The above Expression of Interest is advertised on the Met Office ProContract e-Tendering portal called ProContract. To access and register your interest you will need to log onto the ProContract portal via this link: tenders.metoffice.gov.uk
You may need to search for the Call reference DN517499
You will need to register your company (if you have not already done so) and register your interest against the opportunity before you are able to access the tender documents.
If you require guidance or ‘how to’ instructions – see the supplier manuals on the right-hand side of the supplier home page.
Online Discussions between Bidders and the Met Office:
There is a Discussions function on ProContract which shall be used to provide all further information regarding this opportunity including any changes to time scales, scope or clarifications. This function must be used by bidders to submit all clarification questions.
Eligibility:
The following criteria must be met by UK organisations submitting a bid against Strategic Priorities Fund (SPF) funded Calls to be eligible to apply or be awarded funds against this Call:
- Must be a UK operating and registered organisation.
- Consortium bids are eligible; a lead partner must be nominated for payment and agreement purposes and all parties must be UK operating and registered organisations. Details of all consortium members must be provided.
- Funding can only be used to fund new activity for the costs incurred.
- The activity must last the full duration of the Grant Award Term specified
- There must be a willingness to work with Authority and other organisations and individuals associated with the SPF Programme.