Reducing carbon emissions and securing energy supplies are crucial international goals to which energy demand reduction must make a major contribution. On a national level, demand reduction, deployment of new and renewable energy technologies, and decarbonisation of the energy supply are essential if the UK is to meet its legally binding carbon reduction targets. As a result, this area is an important theme within the EPSRC's strategic plan, but one that suffers from historical underinvestment and a serious shortage of appropriately skilled researchers. Major energy demand reductions are required within the working lifetime of Doctoral Training Centre (DTC) graduates, i.e. by 2050. Students will thus have to be capable of identifying and undertaking research that will have an impact within their 35 year post-doctoral career. The challenges will be exacerbated as our population ages, as climate change advances and as fuel prices rise: successful demand reduction requires both detailed technical knowledge and multi-disciplinary skills. The DTC will therefore span the interfaces between traditional disciplines to develop a training programme that teaches the context and process-bound problems of technology deployment, along with the communication and leadership skills needed to initiate real change within the tight time scale required. It will be jointly operated by University College London (UCL) and Loughborough University (LU); two world-class centres of energy research. Through the cross-faculty Energy Institute at UCL and Sustainability Research School at LU, over 80 academics have been identified who are able and willing to supervise DTC students. These experts span the full range of necessary disciplines from science and engineering to ergonomics and design, psychology and sociology through to economics and politics. The reputation of the universities will enable them to attract the very best students to this research area.The DTC will begin with a 1 year joint MRes programme followed by a 3 year PhD programme including a placement abroad and the opportunity for each DTC student to employ an undergraduate intern to assist them. Students will be trained in communication methods and alternative forms of public engagement. They will thus understand the energy challenges faced by the UK, appreciate the international energy landscape, develop people-management and communication skills, and so acquire the competence to make a tangible impact. An annual colloquium will be the focal point of the DTC year acting as a show-case and major mechanism for connection to the wider stakeholder community.The DTC will be led by internationally eminent academics (Prof Robert Lowe, Director, and Prof Kevin J Lomas, Deputy Director), together they have over 50 years of experience in this sector. They will be supported by a management structure headed by an Advisory Board chaired by Pascal Terrien, Director of the European Centre and Laboratories for Energy Efficiency Research and responsible for the Demand Reduction programme of the UK Energy Technology Institute. This will help secure the international, industrial and UK research linkages of the DTC.Students will receive a stipend that is competitive with other DTCs in the energy arena and, for work in certain areas, further enhancement from industrial sponsors. They will have a personal annual research allowance, an excellent research environment and access to resources. Both Universities are committed to energy research at the highest level, and each has invested over 3.2M in academic appointments, infrastructure development and other support, specifically to the energy demand reduction area. Each university will match the EPSRC funded studentships one-for-one, with funding from other sources. This DTC will therefore train at least 100 students over its 8 year life.

Network science, the study of systems of interconnected entities and their functional interactions, has three principal goals: 1. Discover and enumerate the basic principles of networked systems. 2. Use structure, dynamics, and demographics to infer functional interactions when they are not directly prescribed. 3. Predict network structure and demographics, and use mathematical and computational methods to manipulate existing networks and design new networks with desired properties. Networks provide a powerful tool for representing and analysing complex systems of interacting entities. They arise in the physical, biological, social, and information sciences and can be used to represent interactions between proteins, friendships between people, hyperlinks between web pages, and so on. A network consists of a set of entities (called "vertices") that are connected to each other by ties (called "edges"). Most studies of networks consider static networks with a single type of edge, and numerous tools have been developed to study such networks. However, networks that arise in applications are often more complicated. They can be "dynamic" in that they can have a time-dependent structure, which might represent changes in the committee assignments or voting patterns of politicians over time or different functional connectivity of brain regions during different parts of a motor activity. They can also be "multiplex" in that they include multiple edge types, such politicians who are connected both via common committee assignments and similar voting patterns. Although researchers have long been aware that networks in applications are both dynamic and multiplex, it is only in the past few years that high-quality data has become available to study such situations effectively. I recently helped develop a "multislice" framework for networks, along with accompanying algorithmic tools, which can be used for studying time-dependent and multpliex networks (Mucha et al, Science, 2010). The multislice framework departs from the norm in network science, as it formulates networks using three-dimensional arrays of numbers instead of the usual adjacency matrices (i.e., two-dimensional arrays). The 2010 paper developed a tool in multislice networks for the algorithmic detection of structures known as "communities", each of which consists of a set of vertices that are connected more densely to each other than they are to vertices in the rest of the network. The presence of different types of network edges, which are interrelated and evolve in time, raises conceptual and practical questions about network structure, and the multislice framework can be used to try to answer them. The proof of principle in our 2010 paper paves the way to studying dynamic and multiplex networks in subjects such as biology and political science. However, applying this framework to applications in practice will require considerable effort on both conceptual and application-oriented fronts. The proposed programme will make major headway towards this goal, especially in the area of community structure. Through my collaborations (see Letters of Support), I have access to large data sets from political science and biology. Overcoming the challenging nature of dynamic and multiplex data will yield interesting insights both conceptually and for applications. Much is known about community structure in static networks with only a single type of edge, but almost nothing is understood about community structure in either dynamic or multiplex networks. Most networks encountered in applications have such features, and my proposal directly addresses this issue.

The project 'ENG-EPSRC EFRI ELiS: Developing probiotic interventions to reduce the emergence and persistence of pathogens in built environments' is an international, multidisciplinary research project that addresses contemporary agendas towards designing and buildings healthy built environments. The project brings together expertise in microbiology, the built environment, infectious disease and antimicrobial resistance (AMR). The proposal responds to the urgency for improving the health of our built environments using an approach that departs from the modern understanding that healthy environments should be based on fewer microbes. Urbanisation, indoor lifestyles and ingrained antibiotic mentalities are selecting for AMR and there is a risk that the current pandemic exacerbates our overreliance on antibiotic approaches which are driving other unintended, longer term public health problems. This approach considers a more nuanced understanding of microbes that recognises that not all microbes are pathogenic. In this manner, future healthy buildings should aim to discriminate between good and bad microbes and in doing so, find ways that can reduce exposure to harmful microbes but also permit the presence and agency of benign environmental microbes roles that are beneficial for human health and the resilience of buildings and cites. The proposal will develop novel probiotic materials for buildings that contain living strains of B.subtilis, a soil derived bacteria that exhibits mechanisms which can inhibit the growth of drug resistant organisms. In the laboratory, we will engineer these probiotic materials for application in buildings that can demonstrate long term survival and ability to prevent AMR bacteria colonisation on these materials and on other building surfaces. In the workshop we will develop novel bio-fabrication approaches that will allow for these living materials to be manufactured in to a series of 1:1 living building component prototypes. These prototypes which will include floor and wall surfaces, furniture components and building panels and cladding will undergo a longitudinal microbial study in a real world building environment at OME, HBBE at Newcastle University, addressing longer term questions of how to progress this approach for building application.

We aim to solve computing's most pressing problem - concurrency and distribution - by adapting one of computing's most successful concepts - the data type. Data types codify the structure of data; session types codify the structure of communication. Session types will enable a revolution in the development of concurrent and distributed software, making it cheaper to construct and maintain, and more reliable. Concurrency and distribution are computing's most pressing problem: unless we discover a way to routinely and reliably build concurrent and distributed systems, a half century of unprecedented technical progress will draw to a close. We are approaching the 50th anniversary of Moore's Law, the observation that component counts and clock speeds double every 18 months. No exponential improvement can continue forever, and recently this rule has changed: clock speeds now remain fixed while the number of processors doubles, so exploitation of concurrency is essential. Meanwhile, everyone now has a computer in their pocket, and these computers depend crucially on communication to achieve their function. We inhabit a world of web applications, cloud services, and mobile apps: society increasingly depends on a technological infrastructure of concurrent and distributed systems. Programming concurrent and distributed systems is notoriously difficult. Many solutions are based on shared memory, which requires the programmer to reason about every possible interleaving by which many processors access a common resource. Shared memory scales only to a certain point; it is not appropriate for programming the server farms that drive the web or for mobile applications. The most successful solutions so far appear to be those that replace shared memory with communication as the central structuring technique. Communication usually centres around the notion of a protocol, a series of operations in a specific order. However, direct support for protocols at the language level has been lacking, as compared with data types. The data type is one of computing's most successful concepts. Data types appear from the oldest programming language to the newest, and cover concepts ranging from a single byte to organised tables containing information on customers and orders. Types act as the fundamental unit of compositionality: the first thing a programmer writes or reads about each method is its data type, and type discipline guarantees that each call of a method matches its definition. Data types play a central role in all aspects of software, from architectural design to interactive development environments to efficient compilation. The analogue of the data type for concurrency and distribution is the session type. A session type codifies the notion of a protocol. Session types build on data types, as data types specify the lowest level of data exchange, upon which more complex protocols are built. Just as type discipline matches use and definition of a method, so session types ensure consistency between the two ends of a communication. We expect session types to play a role in all aspects of software. Today, architects discuss the high-level structure of a system in terms of its types, but must resort to informal notions of protocol to describe communication; in future, they will describe communication in terms of session types. Today, programmers use tools that let them search for methods and modules based on their type, and give immediate feedback if their program violates type discipline, but must resort to informal notions of protocol when coding communications; in future, they will search for components based on their session type, and get immediate feedback if their program violates session type discipline. Today, software tools exploit types to optimise code, but cannot exploit the informal notions of protocol to optimise communication; in future, communication middleware will exploit session types to support efficient messaging.

This project examines the effects of US immigration policies on asylum-seekers and transit migrants who have been forcibly returned to Mexico and Guatemala as a result of new third country asylum processing agreements. It explores how they and their families experience risk and insecurity during this process, and also how they may develop coping mechanisms to mitigate these stressful situations. Crucially, it investigates the evolving asylum processing and receiving context in Mexico and Guatemala and interrogates claims that these states are 'safe third countries' for asylum-seekers who wish to come to the USA. It draws upon our previous work on the ways in which asylum governance and the infrastructure for humanitarian protection have been sub-contracted to neighbouring states and uses the insights gained from those studies to inform an investigation into the risks faced by asylum-seeking families and deported migrants in Guatemala and Mexico. Our ambition is for this first stage project to feed into and provide a secure basis for a major follow on research programme in Mexico, Guatemala and the neighbouring states. This first-phase study , carried out by the international team, will involve a multi-method approach including (i) desk-based research (combining policy analysis with key informant expert interviews); (ii) a series of rapid assessments involving analysis of crime statistics; observations of living conditions in Mexico and Guatemala; interviews with families sent to 'safe' third countries; and a gender impact study. These research activities will investigate the risks for asylum-seeking and migrant families; how families navigate these asylum and immigration systems and structures; and the impact of return on individuals and families; (iii) participatory arts-based research activities with children and young people living in a migrant shelter to better understand the impact of displacement and separation on them; and (iv) a policy synthesis of what has been learned from 'safe country and off-shore processing asylum systems in other global settings. Outputs from the study will include an advocacy tool-kit developed from the testimonies of asylum-seeking and migrant adults and children; a series of public engagement and policy events to share knowledge and learning from the work; and a proposal for a larger international collaborative body of research on migration and asylum governance across the region.