National Nuclear Laboratory

NDA PhD Bursary – (G) Open Criteria

This category will be left open for civil nuclear decommissioning related proposals that might be of interest to the NDA and are not encompassed by the above themes. This would also cover research supporting the NDA’s mission in effluent treatment and management and alpha-decommissioning of contaminated plant and wastes. When constructing proposals for the open theme, respondents should ensure their idea aligns with the NDA mission (see NDA Strategy 2021) and demonstrate this in their proposals.

In addition to the proposals outlined, the NDA is specifically interested in research proposals in the following areas:

(G.1) Low CO2e construction for decommissioning

Some civil decommissioning activities will require the construction of substantial infrastructure such as new intermediate storage facilities and eventual disposal facilities. Research is required into how to minimise the carbon footprint of these structures whilst maintaining the necessary engineered levels of confidence during their operational lifespan.

(G.2) Low CO2e alternatives for waste packaging

Nuclear waste packages often have a high CO2e either through the use of energy intensive construction materials for the outer packaging (e.g. steel) or via the waste matrix itself (e.g. grout). These materials are likely to become more expensive or less freely available in the future, as well as contributing to the carbon footprint of the NDA group and our supply chain. Research is required into alternative, low CO2e materials for use in waste packaging that can meet the necessary storage and disposal requirements. This research should consider how to maximise recycling into the process, e.g. through the use of recycled concrete or additives such as graphite

(G.3) “Smart” cement

Aligned with the characterisation theme, the NDA is considering the management of waste packages in storage. There is an interest understanding the feasibility of novel methods that other industries are exploring that could be used to detect, quantify, and manage the contents of cementitious waste packages in storage.

(G.4) Shared Waste streams between decommissioning sectors

The NDA wants to ensure that our mission outcomes and the journey to deliver them are sustainable. Different decommissioning sectors share this objective. Research is required to understand how the concepts of reuse and recycling can be applied to waste streams, particularly those that are shared across different industries, such that the interplay between sustainability benefits and the economic case is understood.

(G.5) Cross industry collaborations

Recognising the cross-industry similarities between the decommissioning missions of the NDA and the oil and gas community, we would be interested to receive research proposals that build on these synergies and address common challenges. More information on the challenges surrounding decommissioning in oil and gas can be found here:

Research – The National Decommissioning Centre (

Whilst this element of call has not been formulated in conjunction with the Net Zero Technology Centre or the National Decommissioning Centre, any relevant proposals will be shared and assessed together with these organisations.

(G.6) The role of artificial intelligence (AI) in risk prediction analytics across the nuclear industry

Reducing both hazard and risk are core drivers in NDA’s mission. Developing improved models to utilise the power of AI in accessing, understanding and running multiple scenarios to potentially output suggestions for risk predictions is an incredible opportunity. The research may cover the data types and values of human created archived data and how AI can deeply analyse the outputs over many decades in the past. Research across many industries on how predictive analytics are being enabled would also be of great value. Also, understanding the leading AI data models and how AI can learn from other AI deployments across aligned organisations and the implications of those outputs. The outputs would also be interesting across the ever-increasing horizon scanning predictive data processing.

For projects relating to applications of artificial intelligence, please refer to and consider the sub-section at the end of this document when applying to the call.

(G.7) The challenge of modelling long term future risk uncertainty

One of the impacts of policy responses to the Covid-19 pandemic has been the increased level economic uncertainty about the future. For all sectors there is a large increase in uncertainty, particularly around spending plans and revenue projections. Research into new models and how we exploit data to help show long term future risk exposures and areas for management are needed. How multiple models could be created to give various confidence level aligned outputs coupled with new analytics platforms would be of great interest. Developing new innovative quantitative models to estimate the likelihood and potential impact of long-term future risks in new ways would add great value to the planning we have in the nuclear industry which is mapping out activities over 100+ years into the future.

(G.8) Psychological safety

Creating a psychologically safe environment within complex organisations is essential for continued success, and this is further enhanced within the context of complex nuclear decommissioning activities.

The extent to which organisational members feel psychologically able to speak up, express their views and challenge the status quo can impact safety related decision making and levels of participation. Research is sought into the mechanisms involved in the creation of high levels of psychological safety and how that influences the way that individuals frame, carry out and respond to organisational requirements. (For example, carrying out safety investigations, reporting of near misses, developing a culture of innovation and the psychological safety barrier to collaboration.)

(G.9) Learning Organisation

Being a ‘Learning Organisation’ informs how a business continually improves itself through using its own experiences and those of others to create its own meaningful knowledge. This is transferred across the organisation to positively impact safety and delivery performance. Further study is required into the attributes and requirements needed in order to install a strong learning organisation, specifically within the high hazard, high reliability context of nuclear decommissioning.

(G.10) Decommissioning culture

Working in a nuclear decommissioning environment is a unique experience where success is linked to subtractive rather than additive activities, often within physically challenging work environments. Does working on nuclear sites undergoing decommissioning require specific approaches to establishing a culture to enable success? What are the implications for leadership activities, setting expectations, and unspoken elements of the employer/employee psychological contract within a nuclear decommissioning environment?

(G.11) Culture & behaviours within challenging environments

Working in a nuclear decommissioning environment is a unique experience where success is linked to subtractive rather than additive activities, often within physically challenging work environments. When working in challenging nuclear decommissioning and remediation environments, what are the specific elements that organisations need to be mindful of when planning and implementing cultural and behavioural strategies? This may include potential impact on morale, recruitment & retention, leadership style and levels of compliance.

(G.12) Knowledge retention

The nuclear industry faces a huge loss of knowledge as the workforce ages and retires, each taking decades of knowledge and experience with them. NDA are interested in research addressing how this technical information is best captured, stored and made readily accessible to those who may find it useful. How can the information augment existing resources such as the nuclear archive, and possible future object collection?

Furthermore, can this structure be used to capture oral histories of the people and communities affected by the civil nuclear industry. How is this ethnographic information best captured, recorded and made available to those who want to access it, and how can we apply this methodology to legacy audio-visual collections.

(G.13) Developing a framework for understanding asset performance improvement opportunities across the NDA group of operating companies

When mission delivery targets are missed by business units, costs and risks can increase. NDA are interested in identifying better ways (such as loss logging and AI) to understand how the associated assets are performing in parallel to capturing and implementing improvement opportunities to reduce any gaps. Further research is required to identify opportunities in the quantification of asset performance in areas such as:

a)         Collation of loss logging and common issues/benefit

b)         AI across condition reports (Atlas)

c)         Strategic planning and policy deployment at NDA

For this research, the PhD researcher could be seconded into the NDA Asset Management & Continuous Improvement (AMCI) team to allow access to real data and real problems and help identify solutions.

(G.14) Developing a performance focused approach and culture for mission delivery improvement

When mission delivery targets are missed by business units, costs and risks can increase. Focus and culture within the industry can negatively impact the required performance where nuclear is seen as different (harder/more complex) when in fact many of the assets and value streams are similar to many other sectors (such as oil and gas). The NDA would like to identify better ways to achieve a performance focused culture for mission delivery improvement.

For this research, the PhD researcher could be seconded into the NDA Asset Management & Continuous Improvement (AMCI) team to allow access to real data and real problems and help identify solutions.

To apply for the scheme, please click here.