Other Training Schemes

The NIHR Imperial BRC is very pleased to announce a collaboration with The Institute of Chemical Biology EPSRC CDT in Chemical Biology – Empowering UK BioTech Innovation (ICB CDT), which will partially fund a total of five studentships recruited via the ICB CDT. There will be three studentships commencing in October 2024, with an additional two to be recruited for October 2025 entry.

The Institute of Chemical Biology (ICB) was created more than 20 years ago with a focus on the development of novel molecular tools and technologies to tackle challenges in discovery and healthcare. It then expanded its focus to include the agri-science and personal care sectors. The ICB CDT is the longest-running CDT in the UK and has graduated >380 PhD students to date, receiving the fifth renewal in March 2024.

The ICB CDT and The NIHR Imperial BRC have co-sponsored the following studentships for October 2024 entry:

Project Title: Target-directed Synthesis of Protein-Protein Interaction Inhibitors

Bracha Lawrence, supervised by Dr Anna Barnard, Professor Alan Armstrong and Dr David Mann, will be exploring how protein-protein interactions (PPIs) play critical roles in many biological pathways, the misregulation of which can result in disease. Therefore, PPIs have long been considered attractive drug targets, but the number of successful inhibitors generated remains limited. Current screening methods using established compound libraries often lack the structural properties necessary to identify inhibitors of the characteristically large and flat interfaces of most PPIs. We will combine the advantages of robotically enabled screening and a novel assay developed in the Armstrong and Mann groups to establish a high-throughput technology for the identification of PPI inhibitors with the target protein present in the screening conditions to enable it to select for its preferred ligands. This will enable the rapid identification of either peptide or small molecule ligands for any target PPI.

Project Title: Visualising the effects of pollution nanoparticles on respiratory epithelial cells at air-liquid interface

Fawaz Raja, supervised by Professor Marina Kuimova, Professor Alexandra Porter, Professor Fan Chung and Professor Ian Adcock, will be investigating pollution nanoparticles, termed particulate matter (PM), carry an enormous population health burden, through direct and indirect effects that are thought to involve oxidation and inflammation. However, currently, there is no single imaging or biochemical technique available to unequivocally assign the exact timing and the (bio)-chemical effects of PM components, thus preventing the implementation of solid strategies for the mitigation of their deleterious effects. This proposal will establish the exact site, sequence and timing of PM interaction with human airway epithelial cells and organelles. By establishing the relationship between these events this work will pinpoint the crucial subcellular processes that lead to oxidative stress and inflammation both at a single cell level and in whole cell populations. We will develop protocols to assess localisation via analytical cryo-electron microscope (cryo-EM) and direct oxidation pathways via fluorescence lifetime imaging microscopy (FLIM) in primary human bronchial epithelial cells (HBECs) grown in submerged culture and at the air-liquid interface (ALI), which is the only model that accurately reflects airway pathophysiology, for the first time.

Project Title: 3D printed synthetic tissues for patterned interactions with cellular populations

Rohan Sekhri, supervised by Dr Ravinash Krishna Kumar, Dr Yuval Elani and Professor Karen Polizzi, will examine cellular communities, consisting of cells (microbial and/or eukaryotic) living and interacting in various environments, are starting to be used in applications ranging from environmental remediation, agriculture, food science, bioproduction, and biomedicine. Moreover, it is increasingly being realized that communities of interacting cells underpin many aspects of human health (i.e. microbiomes). A global research priority therefore is to understand and engineer these communities for our own goals. Patterned population gene expression in cellular communities is critical for the establishment and development of both microbial communities and eukaryotic tissues. However, external control over target-cell populations is hugely limited due to the lack of smart-patterned release systems that can integrate and deliver effector molecules to cells when required. Here we propose to solve this, by using a custom-built 3D printer to build a smart-patterned release system for controlling population gene expression in cells with high spatial and temporal resolution. These printed systems will comprise of 100s of pL-sized aqueous droplets networked by interfaced lipid bilayers, of which we call synthetic tissues. Critically, we will develop these synthetic tissues to function in aqueous environments where encapsulated effector molecules will be released through membrane proteins present in the connected bilayers. Further, we will develop these 3D-printed patterned release systems to be robust and adaptive to their external environment, and validate our system by interrogating patterned gene expression in both defined bacterial and mammalian cell populations.

In the current BRC, we are committed to support the  UKRI Centre AI for Healthcare & UKRI AI Centre in Digital Healthcare (AI4Health) by co-funding five PhD Students. The centre aims to train a new generation of PhD-level researchers, including clinical PhD fellows and allied healthcare professionals, to develop AI systems that address healthcare challenges with a focus on patient needs and societal values.

The UKRI AI for Healthcare Centre was launched in 2019, with ambitious mission and plans to train future AI innovators who transform healthcare through the power of AI, and to create a strong digital healthcare ecosystem, committed to driving advancements in both AI and healthcare, and to transforming health services and patient outcomes. Since then, the Centre has established a leading interdisciplinary PhD research programme. Furthermore, by building on established research collaborations, the Centre has also developed an entire digital healthcare ecosystem of AI and clinical experts, institutions, stakeholders, and networks.

The Training vision

The vision of the centre is to train AI innovators in digital healthcare who will transform the field by leveraging AI’s potential for innovation. In collaboration with partners and sponsors like the NIHR Imperial Biomedical Research Centre, Imperial NHS Trusts, UK regulators, professional organisations and industrial partners, the centre aims to equip AI4Health graduates with the expertise to bridge AI and healthcare disciplines. The graduates should become independent actors in the highly regulated healthcare technology market, therefore becoming leaders and driving impactful advancements through NHS collaborations and global industrial partnerships.

Equality, Diversity, Inclusion

The centre welcomes staff, students, visitors, partners, guests and collaborators regardless of age, disability, ethnicity & race, gender reassignment, marital or civil partnership status, pregnancy and maternity, religion or belief, gender or sexual orientation. Diversity is encouraged and embedded in the teaching and learning strategy and events, with the belief that shared perspectives and awareness of different experiences are essential to becoming better AI researchers and leaders and driving innovation. The centre takes pride in understanding and actively promoting the idea that the diversity of people is not only essential but also inspiring and essential for positive outcomes. This is particularly true in Artificial Intelligence, which has deep ramifications on society and bears the risk of EDI biases being amplified and thus requires EDI awareness from day one.

The Centre has already surpassed UK sector averages by a significant margin. For instance, the ecosystem of the PhD researchers, staff, and research community is notably diverse. This is evidenced by a much higher proportion of female PhD researchers in AI4Health CDT (33%) compared to the UK’s AI researcher sector average of 8.2% (“Where are the women?” report, Alan Turing Institute, 2021) – and also higher than for female AI PhD researchers in the USA (22%; Stanford AI Index, 2021). Moreover, the current AI4Health Cohort have a noticeable proportion of students who identify themselves as non-binary gender (2%). Similar statistics show above-average UK-raised ethnic minority and disability representation.

AI4Health researchers supported by the NIHR Imperial BRC

Adam Tlemsani

PhD project title: Polarization/Spectral Analysis based Surgical Imaging Diagnostics

Abstract: Improving the state of the art in imaging-based diagnostics in surgical imaging by exploiting multichannel information from a combination of polarization and/or spectral imaging of tissue reflectance response during surgical imaging procedure/endoscopy. The goal will be to develop AI techniques to exploit such multichannel information as well as develop techniques to augment limited ground truth (labelled) datasets with synthetic datasets obtained using a combination of computer graphics simulation and generative AI techniques.

Vishal Jain

PhD project title: GigaScale: Pioneering a Robust and Fair Foundation Model for Histopathology

Abstract: We propose to develop new methods for building a multi-modal foundation model in histopathology that can a) handle multi-modal gigascale data efficiently and b) provide new quality assurance methods for generative AI to safeguard critical applications in healthcare and foster fairness and regulatory compliance.

Noura Ezaz-Nikpay

PhD project title: Deep PDE Solvers for Modelling Muscle and Brain Machine Interfaces

Abstract: The development of human-machine interfaces is a field that is highly reliant on simulations of the underlying biophysics. Currently, these models are mainly based on classical methods of solving PDEs which have difficulties simulating complex biophysical systems. However, a new generation of deep energy minimisation methods shows promise as an alternative. The project aims to investigate the potential of these new approaches.

Ashvin Gupta

PhD project title: Interpretable neuro-symbolic approach for predicting pancreatic cancer from high-dimensional health data.

Abstract: 10,000 UK patients are diagnosed annually with pancreatic cancer, with only one-third of patients diagnosed at early stage (I-II) contributing to some of the lowest age-standardised 5-year cancer survival in Europe (8%). A third of patients present three or more times before referral by their GP.  This proposal aims to learn rich models from multimodal health data to be used in conjunction with explainable computational rules from guidelines for better early-stage predictions..”

Felix Oury

PhD project title: AI-based personalised prediction of asthma attacks in children

Abstract: Asthma is the most common childhood long-term inflammatory airway disease. Unpredictable asthma attacks cause sudden worsening of symptoms and may be fatal. Current routine treatment using inhaled corticosteroids and bronchodilators prevents asthma attacks in only 68 per cent of patients. We aim to achieve asthma control by developing an AI-based predictive model for asthma attacks using our unique longitudinal data collected in the paediatric difficult asthma clinic at the Royal Brompton Hospital.

The NIHR Imperial BRC is delighted to be able to award up to four bursaries to home fee status participants of the MRes in Clinical Research – Translational Medicine pathway programme for the 2024/2025 academic year.

Eligibility

Bursaries are available to those currently holding an offer for the 24/25 academic year to start the MRes Clinical Research Programme (Translational Medicine pathway). The funding will only be available to Home status fee-paying applicants who have a current Imperial College Healthcare NHS Trust association or have worked at the Trust within the past 5 years at any level.

Funding

Up to 4 bursaries are offered to home fee-paying students, valued at £7,450, with 50% of the award applied for the 1-year programme.

Eligibility criteria

• To be eligible to apply the applicant must be in receipt of an offer for the MRes Clinical Research – Translational Medicine to commence in October 2024.
• To receive the bursary, you must have accepted the offer and have fulfilled all offer criteria.

Application process

Applications for the MRes Programme can be made online. As part of your application please include a 1-page personal statement outlining your reasons for wishing to undertake the programme and at the top of this document clearly note your application is related to this BRC funding opportunity.

You do not need to make a separate application for the funding – your application for the MRes programme will be taken as an application for both the MRes programme and to be considered for the funding.

Deadline

Please ensure you have submitted your application no later than Friday 23^rd August 2024, 12.00 pm (UK time). Please note that this funding opportunity may close earlier if all 4 bursaries have been allocated, so applicants are encouraged to apply early.