STRIDE 2026 Call for Projects

1) Dr Haidar Hassan

Email: h.hassan@qmul.ac.uk

Project Title: Bridging the Hematology-Chemistry Divide: A Feasibility and Cost-Benefit Analysis of an Integrated 'All-in-One' Point-of-Care Diagnostic Device

Project Statement: Current diagnostic pathways for obtaining a comprehensive health profile (CBC, Lipid Panel, Vitamin D) are fragmented. Clinicians must use three separate point-of-care (POC) devices or central laboratories, increasing costs and delaying "vein-to-brain" time. Currently, no market-ready device integrates Haematology (cellular analysis) with Clinical Chemistry (plasma assays) due to the "Sample Prep Conflict" - conflicting requirements for whole blood versus plasma separation. A comprehensive POC tool would streamline treatment pathways, specifically for Oral and Maxillofacial surgery and inflammatory index monitoring. 

2) Dr Haidar Hassan

Email: h.hassan@qmul.ac.uk

Project Title: Evaluating the Feasibility and Cost-Benefit Analysis in a Fully Digitised Printed Surgical Workflow

Project Statement: Virtual surgical planning and 3D printing have gained popularity as its evidence multiplies. Optical impressions and CBCT imaging help create custom surgical guides, anatomical models and implantable components; however, the overall process remains fragmented. Most hospitals rely on external manufacturers and third-party software which causes delays, added costs, and hinders widespread adoption. This project aims to evaluate the technical feasibility and economic value considerations required to establish a fully digitised, in-house 3D-printed surgical workflow. 

1) Dr Ana Caetano    

Email: a.caetano@qmul.ac.uk  

Project Title: Neuronal mechanisms in oral barrier function

Project Statement:

The peripheral nervous system (PNS) is among the most adaptable cellular systems in the body, yet its role in shaping epithelial development and maintaining tissue integrity remains poorly understood. In the oral mucosa, diverse neuronal and non-neuronal populations arise early in development, but their contributions to tissue architecture, barrier resilience, and long-term homeostasis have not been fully defined. Given the oral epithelium’s essential role in feeding, breathing, and speech - and its remarkable ability to withstand continuous microbial, chemical, and mechanical challenges with minimal scarring - understanding how its neural components develop is of significant biological and clinical interest.

This project will apply genetic fate-mapping strategies to trace the temporal dynamics of neural circuit assembly within the developing oral mucosa. Using multiplex immunohistochemistry, high-resolution imaging, and computational analysis pipelines, the intern will investigate changes in the identity, distribution, and developmental potential of neuronal and non-neuronal progenitor populations. The short project timeline focuses on generating preliminary maps of lineage-labelled cells, quantifying key developmental markers, and identifying candidate patterns that may regulate oral nervous system maturation.

Over the 8-week period, the student will gain hands-on experience in tissue processing, fluorescence microscopy, image segmentation, and data interpretation. By the end of the internship, the student will produce an annotated dataset, a preliminary figure set, and a concise summary of findings that will contribute to ongoing efforts to uncover how neural elements shape oral mucosa homeostasis and how their dysregulation may influence disease states such as oral cancer.      

2) Dr Ali Golkari

Email: a.golkari@qmul.ac.uk 

Project Title: AI-Supported Orthodontic Treatment Need Decision-Making 

Project Statement: This project aims to support an ongoing clinical research programme investigating the use of artificial intelligence (AI) to enhance orthodontic treatment need assessment and referral decision-making. If the project proves successful, it will improve the appropriateness, safety, and quality of patient care. Inappropriate or inconsistent orthodontic referrals can contribute to inefficiencies in care pathways, delayed treatment, and unnecessary burden on specialist services. AI-supported referral tools have the potential to assist clinicians by standardising decision thresholds and improving referral quality, but their development requires robust, well-curated clinical image data and an understanding of real-world referral pathways. 

During the 8-week STRIDE studentship, the student will first gets familiarized with the concept of project and its process, then will contribute to early-stage clinical research activities aligned with the initial phase of this project. Specifically, the student will support the collection, organisation, and quality assurance of orthodontic clinical images obtained as part of a live research study commencing in parallel. Under supervision, the student will assist with categorising images according to established orthodontic referral criteria and mapping current referral decision points to inform future AI-supported workflows.                                         

3) Dr Cecilia Gonzales-Marin

Email: c.gonzalesmarin@qmul.ac.uk           

Project Title: Periodontitis as a risk factor for dementia   

Background: This ongoing project investigates Periodontitis, a chronic inflammatory condition of the supporting tissues of the teeth, as a potential risk factor for dementia. The overall aim(s) of the study is to explore associations between periodontitis and cognitive function in a cross-sectional observational clinical study, as well as to identify specific periodontal pathogens capable of contributing to the pathogenesis of dementia. This is a pilot study that aims to gather data for future observations and/or interventional studies. The studentship's purpose is to get the student exposed to the complexity of levels that takes part in clinical research. The student will become part of the research team and will support recruitment of participants and sample collection at the Royal London Dental Hospital, as well as shadowing the laboratory analysis of samples, and data interpretation. Before starting, the student will require to complete training in the aspects of clinical research obtaining a clinical governance certification, training on sample handling, and all aspects of ethically performed clinical research. 

                        

1) Dr Judith Edwards and Dr Raul Szekely

Email: Judith.Edwards@qmul.ac.uk and Raul.Szekley@qmul.ac.uk  

Project Title: Identifying and Understanding Equity Considerations for Implementing and Using a Digital Health Intervention for Type 2 Diabetes Distress in Primary Care

Project Background: This project explores how and where digital health interventions (DHIs) for emotional wellbeing can be inclusively integrated into primary care (PC) pathways for type 2 diabetes (T2D) in England. This application proposes two interns working together to realise a common aim. Interns will undertake complimentary yet distinct roles, with independent research objectives, methods and learning outcomes, before synthesising findings in joint mapping processes. The proposal builds on a current QMUL Centre for Primary Care study (DWELL-QME25.1192) aiming to develop a DHI for people living with T2D-related emotional distress. This joint-internship focuses on two DWELL identified knowledge gaps, for which interns will undertake differing activities within their respective roles. 

2) Dr Jessica Ashurst

Email: jessica.rees@qmul.ac.uk  

Project Title: CancerLearn project to improve cancer diagnosis for people with a learning disability

Project Background: The overall aim of the CancerLearn project is to improve cancer diagnosis for people with a learning disability. We will be halfway through data collection for our ethnographic case study. Here, we will be collecting data from three areas across the UK about ways health and social care services are supporting people with a learning disability going through diagnosis of medical symptoms. This will involve interviews with staff and people with a learning disability (and their supporters), observations of practice, and shadowing people with a learning disability through their diagnostic journeys.  

The STRIDE participant will gain a variety of skills from working in a diverse team of health services researchers focused on addressing inequalities. In this placement, the participant will be introduced to ethnographic methods and how they are applied in a healthcare setting to answer research questions. They will gain an understanding of what it is like to live with a learning disability, and the common types of cancer (and how they are diagnosed) for this group. The participant will gain a detailed knowledge of the research process through hands-on experience, shadowing an experienced qualitative researcher during recruitment, data collection and analysis.  

1) Dr Patrick McGurk

Email: p.mcgurk@qmul.ac.uk 

Project Title: Student Knowledge Exchange: what is the ‘real’ student learning journey

Background: Student Knowledge Exchange (SKE) is an increasingly important  approach to learning in higher education. It is characterised by student-led external projects, typically involving community partners, facilitated by both practitioner mentors and  university educators. Of the several stakeholders in SKE, students’ experiences are the least  understood, particularly with regard to their own agency and inclusion. Conventional  evaluation frameworks that seek to measure student outcomes do not satisfactorily capture  students’ lived experiences of SKE, which anecdotal evidence suggests can be  transformative, especially when working with community partners, although also potentially  exclusionary.  
 
This project will pilot a participatory methodology to better understand variation in  students’ lived experiences of agency and inclusion in SKE. The STRIDE researcher will be a  former participant of SKE. They will lead a half-day reflection workshop, conduct  approximately 15 interviews with students and assist with thematic analysis of the data.  Participants/interviewees will be alumni from the QMUL SKETCH projects Project ReMake, in  which Business and Law students worked together with ex-offenders on their  entrepreneurial business plans, and/or the Windrush Justice Clinic project, in which Business  and History students worked together with local campaigners (qmul.ac.uk/sketch). 

2) Dr Sianne Gordon Wilson

Email: S.Gordon-wilson@qmul.ac.uk 

Project Title: Digital Sustainability Research: Social Media, Emotions, and Pro-Environmental Behaviour

Project Statement: This project investigates how digital environments shape sustainable behaviours, focusing on the interface between social media, emotional engagement, and sustainable communications. The research has three core goals: 

(1) to understand how different social media platforms influence the effectiveness of sustainable communication; 

(2) to explore the role of emotions in Gen Z’s unsustainable online habits using existing interview data; and 

(3) to examine how platform-specific content can encourage pro-environmental behaviours, with a particular focus on water conservation. 

The qualitative data for the first two projects has already been collected through semi-structured interviews, enabling the intern to focus on deepening the theoretical and analytical understanding of these topics. The third project will involve them participating in the design of small-scale behavioural experiments, including the development of visual and message-based stimulus scenarios across different platforms. This will give them hands-on experience of how digital content is developed, adapted, and evaluated in research settings. 

 

1) Dr Angela Dunstan

Email: a.dunstan@qmul.ac.uk     

Project Title: Imagining the Estuary: Thames Animal Encounters in Victorian Literary and Visual Culture 

Project Background: This project investigates how nineteenth-century writers imagined and represented the Thames Estuary through their encounters with animals, with particular attention to East London, where the tidal river, docks, and marshlands created a distinctive and ecologically sensitive environment for human-animal interaction. Focusing on both everyday and extraordinary sightings – from eels, whitebait, and gulls to porpoises, seals, the occasional whale, and even imagined creatures – this study explores how these representations shaped Victorian perceptions of the Thames as a dynamic and biologically complex system. Central to the project is the concept of the 'imaginative estuary', the cultural zone where environmental reality, ecological processes, literary expression, visual imagery, and urban experience converge. 

Over an eight-week period, the student researcher will help build the project's primary source base by: 

1. collecting and cataloguing newspaper accounts of animal sightings and riverine 'marvels', with a strong focus on East London;
2. identifying Victorian texts that describe or respond to animals in these environments; 
3. sourcing visual materials from digital databases and museum collections;
4. gathering contextual materials on fisheries, pollution, habitat change, and estuarine ecology; and
5. producing an initial map of animal-related events in East London’s tidal reaches. 

The student researcher will compile a digital archive of textual and visual materials and assemble a thematic map visualising ecological and cultural patterns of sightings and stories. By the end of the eight weeks, they will have gained skills in archival research, textual and visual analysis, and environmental-humanities methods, contributing to an interdisciplinary investigation of how animals shaped the cultural imagination surrounding the nineteenth-century Thames Estuary. 

1) Dr Giuditta Trinci

Email: giuditta.trinci@qmul.ac.uk 

Project Title: From Catchment to Estuary: Land Use and Human Activities Driving Sediment and Water Contamination

Project Statement: Estuaries and saltmarshes are critical ecosystems that support  biodiversity, provide vital ecosystem services, and store large amounts of carbon. However, these areas are increasingly threatened by human activities, particularly land use changes and wastewater discharge, which contribute to heavy sediment contamination. Understanding how these factors influence sediment quality, and the geomorphology of saltmarshes is crucial for managing estuarine health and mitigating the impacts of environmental degradation. 

This project will explore the impact of land use and human activities—especially  wastewater treatment—on sediment contamination in estuaries via the river continuum. The aim is to investigate the semi-empirical relationship between land-use changes and sediment contamination, and how these changes affect saltmarsh erosion.  

The primary objective is to identify and map both diffuse and point sources of pollution along the river system, tracking their migration downstream to the estuary. The project will examine how variations in land use—such as agriculture, urban development, and industrial activity—correlate with concentrations of nutrients, metals, and organic pollutants in river sediments.  

The project will generate quantitative data on how different land uses (agriculture,  urban development, industrial zones) contribute to sediment contamination along the river continuum, identifying the most significant sources of pollutants (e.g., nutrients,  metals, organic contaminants) in both soils and water. 

1) Dr Isadora Cruxen and Dr Emilia Simison 

Email: i.cruxen@qmul.ac.uk and e.simison@qmul.ac.uk     

Project Title: Exploring the outcomes of financialised water provision in Brazil

Project Statement: This project will involve a student in an ongoing study examining how private investment and new governance institutions shape the provision of water and sanitation services in Brazil. Following a major national reform in 2020, Brazil introduced regional “blocks” of municipalities to attract private capital and extend public services to lower income and more vulnerable communities. This reform has accelerated institutional experimentation and growing financial interest in infrastructure assets. The STRIDE student will contribute to analysing these developments by working with longitudinal, publicly available data from the National Information System on Sanitation (SNIS), which reports service coverage, quality, investment, and cost information for all providers since the late 1990s. 

The eight-week project will focus on mapping regional differences in water and sanitation provision and assessing how different ownership structures and types of public-private contracts relate to these variations. Working alongside two supervisors – one from the Department of Sociology, Politics and International Relations (SPIR) and the other from the School of Business and Management (SBM) – the student will process and analyse the SNIS data, discuss questions and emerging results, and elaborate descriptive statistics and visualisations that could contribute to future publications. 

By the end of the project, the student will have gained experience in handling large datasets, applying social science research methods to a real-world policy problem, and understanding how institutional reforms and private investment structure access to essential public services for sustainable development. The project is feasible within eight weeks and offers clear opportunities for student-led insights. 

1) Professor Caroline Morris

Email: C.Morris@qmul.ac.uk      

Project Title: Working as Women Lawyers in the Inter-War Years

Project Statement: The study of early women lawyers is a growing and very active field.  It has been stimulated by a number of recent centenary celebrations eg of the 1919 Act  permitting women to train as lawyers, and their subsequent admission to the profession in 1922.  There have been a lot of publications in this area eg the recent biography of Chrystal Macmillan, and the Women's Legal Landmarks series has featured many women lawyers (vol 3 is currently in preparation). There is a steady programme of events in the field, as well, not only book launches, but workshops, such as the Women's Library course at the LSE on studying women's history (January 2026).  In short, there is an active research community which the student can be a part of. 

1) Dr Lin Su 

Email:  lin.su@qmul.ac.uk 

Project Title: Bioelectronic Sensors for Lanthanides

Project Statement: The global demand for rare earth elements, particularly lanthanides (Lns), is constantly increasing, yet their supply is often compromised by geopolitical tensions. This situation creates an urgent need for effective methods to detect and recycle these critical materials. A key breakthrough in this area has been the recent discovery of Lanmodulin, a protein that has paved the way for developing novel biosensors for lanthanides. While recent research has utilized protein switches for colorimetric and electrochemical quantification of Lns in solution, these existing methods suffer from significant drawbacks: their signals are either not directly readable in a digital format or they require lengthy waiting times for measurement, limiting their practical application. 

Research Aims: The primary objective of this project is to build a fast bioelectronic sensor capable of measuring lanthanides in real time. To achieve this, we will engineer a novel protein switch by modifying a ferredoxin (Fd) protein with Lanmodulin, which will serve as the specific rare earth metal sensing component. The central hypothesis is that Lanmodulin will bind to target lanthanide ions, inducing a structural change in the Fd protein. This modified Fd is a key component of a synthetic electron transport chain we have programmed in Escherichia coli, which is designed to produce an electrical current in response to specific chemicals. The goal is to leverage this mechanism to create a "yes or no" bioelectronic sensor based on the activation of the Fd switch. 

Methods and Techniques: This is an inherently interdisciplinary project that integrates microbiology, synthetic biology, and bioelectrochemistry. The student will gain hands-on proficiency in a range of cutting-edge techniques. Core skills will include learning how to grow and maintain bacterial cultures, perform plasmid editing, and potentially adapt the protein engineering workflow using CRISPR-based genome editing in E. coli. Furthermore, practical skills will be developed in bioelectrochemistry, which are essential for measuring and characterizing the sensor's electrical output. 

2) Dr Giorgia Michelini 

Email: g.michelini@qmul.ac.uk 

Project Title:  An inclusive approach to measuring depression in neurodivergent young adults from diverse backgrounds

Project background: The internship will provide exposure to different research roles, perspectives, and career pathways. The intern will be based within Dr Michelini’s group, an active, interdisciplinary research group focused on neurodevelopmental conditions and mental health across the lifespan (www.trend-lab.net) within the Psychology Department’s Centre for Brain and Behaviour. The group includes 8 postgraduate researchers and peer researchers with lived experience. Dr Michelini’s group is also part of the larger multi-group Cognition and NeuroDevelopmental in Youth Lab within Psychology, bringing together experienced and early-career researchers in youth development and mental health.  The intern will share an office with post-graduate and post-doctoral researchers and placement students in these teams, enabling collaboration and a sense of community. They will receive day-to-day supervision by Dr Michelini and a PhD student in the team, providing structured guidance on research perspectives and methods, continuous feedback, and opportunities to contribute meaningfully to research outputs (i.e., paper co-authorship). The intern will participate in weekly team meetings, be involved in public engagement/science communication activities, and be encouraged to attend research seminars, providing exposure to ongoing research in psychology and neuroscience more broadly.

As the Deputy Lead of the Centre for Brain and Behaviour, Dr Michelini will also connect the student with other placement and postgraduate students working in the Centre, facilitating networking and informal discussions around career options and possible job opportunities. Support will be adapted to the student’s prior experience and career interests, with advice and support in applications for postgraduate studies/training and job applications. 

This project aims to develop a new assessment tool to detect depression in neurodivergent young adults from a wide range of ethnic backgrounds. Depression is frequently under-recognised or missed entirely in neurodivergent people, contributing to delayed access to support and elevated suicide risk. A key reason for this is that existing depression assessment tools do not adequately reflect how depression is experienced and expressed in neurodivergent individuals, particularly those from minority backgrounds. Through our recent research and community involvement work, we have identified distinct and underrepresented features of depression in these groups. This project will use these findings to co-produce a new, more inclusive depression assessment tool.

Over the 8-week placement, the student will work closely with our team and peer researchers with lived experience to co-produce the assessment. The student will support recruitment of neurodivergent young adults, help organise and co-facilitate four co-production workshops, and assist with qualitative analyses. They will also contribute to drafting assessment items that reflect neurodivergent experiences of depression and help coordinate a Delphi study involving experts by lived and professional experience, leading to a new consensus-based assessment. Finally, they will contribute to organising a public webinar to share our findings.

 

 

1) Dr Fatma Benkhelifa        

Email:  f.benkhelifa@qmul.ac.uk

Project Title: LoRa-Based Satellite Ground Station Development and Link Analysis using the TinyGS Network

Project Statement: This project will explore real-world space communications by developing and analysing a low-cost LoRa-based ground station using the global open TinyGS satellite network (or equivalent). Over eight weeks, the student will build a functioning TinyGS transceiver to capture real telemetry from orbiting Low Earth Orbit (LEO) satellites operating typically at 401-437MHz. 

The primary goals are to:

1) Establish and calibrate a reliable receiving ground station 

2) Collect and analyze received signal data such as timestamps, received power, signal-to-noise ratio and Doppler shift from multiple satellite passes, 

3) Compare the real-world measurements with theoretical link budget and Doppler shift across multiple satellite passes. 

4) Evaluate the impact of antenna type (whip, Yagi and patch) on link performance. 

In parallel, the student will develop Python scripts to automate data collection and visualization and write a controlled transmission script for test uplinks within regulatory limits (real-world uplink tests are subject to obtaining or working under an amateur radio license). 

Expected outcomes include a fully operational TinyGS station, automated data collection scripts, analysis for signal and Doppler tracking, and a comparative report linking measured and theoretical results. 

This project offers a unique opportunity combining hands-on hardware experience with theoretical and analytical work, enriching the student’s engineering skills in RF systems, data analysis and regulatory satellite practice.

If desired, the student will complete entry-level amateur radio license training, enabling future transmit experimentation under supervision. 

2) Dr Raymond Hu

Email: r.hu@qmul.ac.uk

Project Title: Tools for safe specification and implementation of distributed software protocols using Multiparty Session Types (MST)

Project Statement:

Aim: Develop a publicly accessible Web interface for learning and using practical software engineering tools based on the supervisor's work in the research area of MST. The target users will be both researchers and real-world software developers.  

Research goals for the project/intern:

• Learn the basic (practical) fundamentals of MST. 
• Adapt an existing or develop a new core MST-based toolchain suited to Web hosting. 
• Develop a Web app and ergonomic user interface for using the tools. 
• Setup a rigorous test framework for the core toolchain and Web app, including using them to specify and implement showcase example applications. 
• Write tutorials explaining the (practical) fundamentals of MST and how to use the Web tools. 

 

1) Dr Eldad Avital

Email: e.avital@qmul.ac.uk 

Project Title:  Domestic Water Recycling

Research Goals: The student will join an active research group that works across fluids, water engineering and sustainable energy. The group includes the supervisor, two current doctoral researchers and an incoming postdoctoral researcher, ensuring the student is supported by researchers at different career stages.

The student will receive frequent guidance from the supervisor and consistent day to day support from a doctoral researcher with experience in applied fluid mechanics and design. At the start of the placement the student will receive training in literature searching, basic fluid flow estimation and the use of computer aided design tools for creating simple components. The supervisor will hold weekly meetings with the student to review progress, address questions and provide guidance on structuring the work. Additional technical support will be available throughout the week, allowing the student to consult on calculations, design decisions and the interpretation of results. The student will also be encouraged to take part in group meetings and informal discussions within the wider fluids and energy community, giving them a sense of how engineering research is carried out in practice.

All required software, computing facilities and design tools will be available to the student during the project. Any consumables needed for simple prototype pieces or three-dimensional printed components will be supported through existing research funding. This structure ensures that the student receives strong academic, technical and peer support throughout the entire eight-week period and gains meaningful research experience within a collaborative environment. 

2) Dr Eldad Avital

Email: e.avital@qmul.ac.uk 

Project Title: Offshore Aquaculture Renewables

Project Statement:  The student will join an active and expanding research group that works in fluids, renewable energy and offshore engineering. The group includes the supervisor, two doctoral researchers and a new postdoctoral researcher who will work closely with the student throughout this project. This ensures that the student is surrounded by researchers who can provide daily guidance as well as broader academic support.

At the start of the project the student will receive training in researching offshore aquaculture systems, assessing wave and wind resources and performing basic energy calculations. Weekly supervision meetings will help shape the student’s work, clarify questions and guide the development of a clear engineering approach. The postdoctoral researcher will provide regular assistance with renewable resource assessment and interpretation of results. A doctoral researcher working in wind energy will support the student in understanding fundamental aerodynamic principles that relate to offshore wind supply.  The student will also be encouraged to attend group meetings and informal discussions within the wider fluids and energy community. This will give them experience of an active research environment and exposure to related areas of ongoing work.  

All required software, data sources and computing resources will be made available. Consumables or minor materials needed for the project will be supported by existing research funding. This structure ensures that the student receives comprehensive academic and technical support and gains a meaningful introduction to offshore renewable energy and aquaculture engineering. 

3) Dr Shaheer U Saeed

Email: shaheer.saeed@qmul.ac.uk 

Project Title: Developing AI tools for image-based diagnosis

Project Statement: The student will be based at the Centre for Bioengineering and will join an interdisciplinary group focused on AI for medical imaging, working alongside PhD students, postdoctoral researchers, and collaborating academics (including Caroline Roney from DERI and Zion Tse from SEMS). The project builds on an ongoing clinical trial from which ultrasound data have been gathered; these will be organised and made accessible for the student at the outset. The student will be embedded in an environment that bridges technical innovation with clinical application.  Clinical Engagement: We work closely with clinicians at UCLH and the Policlinico of Milan, whose expertise informs interpretation of the imaging data and clinical relevance of results.  

The student will engage with these collaborators through discussions and feedback sessions, and, if feasible, a site visit to UCLH to gain insight into clinical workflow.  Supervision and Support: I will provide weekly supervisory meetings, research guidance, and day-to-day technical support. The student will also benefit from mentoring from group members with strengths in machine learning, high-performance computing, and biomedical imaging. I will contribute up to £1000 from flexible research funds to support the studentship.  Training and Development: The student will receive practical training through a dedicated session on high-performance computing, followed by hands-on experience in data preprocessing, model development, and scientific communication. We intend for the work to culminate in a conference presentation or publication. Through the project, the student will gain valuable skills in technical research, collaboration with clinicians, and presentation of research findings. 

3) Dr Giuseppe Viola

Email: g.viola@qmul.ac.uk 

Project Title: Synthesis, Fabrication and Characterization of Novel Antiferroelectric Materials

Project Statement: 

This project aims to continue the successful work initiated last year by another STRIDE student, who remains actively involved, preventing project fragmentation, ensuring a coherent handover and research continuation. The new candidate will take the project forward from the point reached by the current student. The focus of this research streamline is the development of novel ceramic compositions predicted to be antiferroelectric and to undergo reversible electric-field-induced transitions, making them highly suitable for high-density energy storage capacitors. 

Within the 8-week timeframe, it is foreseen that the new student will undertake the following key tasks: 

• Sintering of the developed ceramic powders using both conventional and novel methods, including spark plasma sintering. 
• Characterization of the sintered ceramics' density, phase, and microstructure via the Archimedes method, X-ray diffraction, and electron microscopy. 
• Characterization of the ceramics' electrical properties using impedance spectroscopy (to assess dielectric properties) and current-polarization-electric field hysteresis loops (to confirm or disprove antiferroelectric behaviour). 

The characterization results will be used in a direct feedback loop to optimize the sintering conditions. 

1) Dr Thomas Prellberg

Email: t.prellberg@qmul.ac.uk 

Project Title:  Combinatorial search algorithms - AI and Machine Learning vs Integer Optimization 

Project Statement: This research internship will explore how modern tools such as Large Language Models compete against traditional methods such as state-of-the-art constraint programming  [3]. Based on code made available on GitHub [4,5], this project seeks to explore in the context of the no-three-in-line problem [6] whether PatternBoost [1] or FunSearch [2]  provides a viable alternative. 

The project will be structured as follows: 

• ⁠implement recursive search for the no-three-in-line problem
• implement integer programming for the no-three-in-line problem using CP-SAT
• understand the implementation ofPatternBoostor FunSearch by exploring provided case studies 
• implement the no-three-in-line problem with AI/ML
• ⁠provide a GitHub repository for the project

The main work for this project will be coding in Python, but some of the work may involve modifying existing Julia code. Knowledge in Python (e.g. by having taken  MTH4000 and MTH5005) is required, and a willingness to learn Julia is expected. 

[1] F. Charton et. al., "PatternBoost: Constructions in Mathematics with a Little Help from AI", https://arxiv.org/html/2411.00566

[2] J. S. Ellenberg et. al., “Generative Modeling for Mathematical Discovery”, https://arxiv.org/abs/2503.11061

[3] https://developers.google.com/optimization/cp/cp_solver

[4] https://github.com/zawagner22/transformers_math_experiments

[5] https://github.com/kitft/funsearch

[6] "Gurobi vs the no-three-in-line problem", https://11011110.github.io/blog/2018/11/12/gurobi-vs-no.html