Drugs are often delivered as salts because of their improved solubility profiles. Salts, however, are more likely to be hydrated than solid forms of neutral components. In this project, we seek to better understand the hydration propensity of pharmaceutical salts from a structural viewpoint using a combination of approaches from database analyses to experimentation.

The project is about using galaxy formation simulations to study the effects of energy injection by Active Galactic Nuclei (AGN) on the properties and evolution of galaxies. We will develop models for AGN feedback that are better physically motivated compared to models generally used currently, and investigate their effects. In particular, we plan to model feedback due to winds from AGN accretion disks, and compare to feedback by AGN jets. The AGN feedback models will be implemented in cosmological simulations of galaxy formation using the SWIFT code.

The PhD student will develop and design an eco-friendly rechargeable battery. Artificial Intelligence will be used to design the system based on existing scientific and industrial data. It is highly desirable to use rechargeable batteries to store energy from renewable sources and in consumer electronics and automobiles. This market is dominated by lithium-ion batteries (LIB) which have high efficiency and long life cycles. LIBs are expensive, scarce, and recycling them has a large environmental impact. Using inverse engineering and deep learning, we aim to design next-generation batteries with minimal environmental impact. The successful candidate will combine data analyses with Deep Learning methods and experiment with the state-of-the-art fabrication facilities available at Durham. The candidate will have the opportunity to develop a novel model that correlates the properties of batteries to the composition of materials. This model will also consider the environmental impact of all processes in detail. Because the project has industrial support, the candidate will work closely with the company (WeLoop) to assess the life cycle assessment of existing batteries as a tool to design the next generation batteries. To be successful, a broad skill set is essential, as well as an enthusiasm for experimentation, coding/simulation, and practical engineering.

Stroke care is the fourth biggest killer in England and Wales, and the third in Scotland and Northern Ireland. There are over 1.2 million stroke survivors in the UK; 80% suffer from motor impairment, and 74% require long-term support with basic daily activities. Motor function can be improved with physical therapy. Research indicates that in the UK stroke survivors do not receive the recommended amount of therapy. The reasons are complex but include costs and availability of physiotherapists. Emerging technologies, such as Virtual Reality (VR), offer a potential long-term cost-effective method of providing support to healthcare professionals. One approach is to use Time-of-Flight (ToF) cameras (e.g. Microsoft Kinect) for human pose estimation and motion tracking to enable accurate assessment of patients. These systems offer a way for patients to complete rehabilitation exercises at home. It also gives real-time feedback to encourage patients to stick with their rehabilitation programmes. Other emerging technologies, such as Virtual Reality (VR), have also been researched as a method of assisting rehabilitation efforts. In a VR environment, the interactions taking place can much more closely represent real life as opposed to traditional computing systems. The idea is that encouraging more lifelike interactions, with exercises mimicking Activities of Daily Living (ADL), can not only provide substantial support for standard rehabilitation regimens but also increase patient engagement. Nevertheless, assessing the difference made by physiotherapy and other rehabilitation methods remains unreliable. One study looked at the differences between patient self-assessment, physical therapist assessment and posturographic measures when assessing patient performance. Findings indicate that current methods of assessment suffer from a lack of objectivity and are likely affected by biases. Electroencephalograms (EEG) have been utilised to measure brain activity throughout rehabilitation from brain injury. Studies suggest that it is possible to use EEG biomarkers to predict motor recovery in patients following a stroke. This information might facilitate the tailoring of patient rehabilitation programmes based on the brain activity of patients. While the existing research into technologically aided rehabilitation has shown promising results, most use one method of assessment/tracking. Recent studies have suggested that a multi-domain approach is beneficial providing objective, comprehensive and personalised feedback on patients undergoing rehabilitation for brain injury. Existing approaches are high cost and the number of sensors attached to patients can lead to discomfort. Many of these drawbacks are surmountable using emerging technologies such as ToF cameras. Pose-estimation/motion tracking, EEG and VR offer a means of providing patients with more engaging exercises. In addition, a greater amount of quantifiable data about the condition of patients will be available to aid clinicians and improve patient compliance. The overall aim of this research is to analyse patient recovery from stroke, and other brain injuries, to assess their current state and to assist in making recommendations for recovery. The objectives are 1. To bridge the gap between standard neuro-motor rehabilitation methodologies and new technologically aided methodologies. 2. Improve patient engagement and adherence to home rehabilitation exercise programmes. 3. Provide an accurate and quantitative assessment of the patient's neuro-motor capabilities.

We propose to carry out a large field trial in The Gambia, West Africa, to find out whether there is any additional benefit of spraying homes with DDT in addition to the normal practice of getting everyone to sleep under bednets impregnated with long-lasting insecticides. The study will have two groups of villages: one with only treated nets and the other with both treated nets and DDT spraying. We will measure how effective the interventions are by sampling mosquitoes in the houses and measuring malaria in study children in both sets of villages. Importantly we will determine whether the vectors are likely to become resistant to the insecticides used and we will be able to determine how much it will cost to prevent cases of malaria using the DDT. This study is important since many Afircan countries, including The Gambia, are either spraying houses with DDT at present or intend to do so in the near future.