Applications are now closed. Up to 18 PhD studentships are available at the University of Nottingham, funded by the Engineering and Physical Sciences Research Council.
Starting in October 2019, the studentships are offered through cohort-based doctoral training programmes. They span six distinct themes, with each theme led by an academic expert and offering up to three fully funded opportunities.
Astromedicine and astro-pharmacy
“We came all this way to explore the moon, and the most important thing is that we discovered the Earth.” – William Anders
How will we colonise Mars? At a time when the world’s space agencies have formed the Global Exploration Roadmap for the long-term human habitation of the planet, this doctoral training programme is focused on addressing this problem.
Achieving this goal requires an interdisciplinary approach. This includes the development of new ways of thinking that are better-able to tackle the engineering and physical science challenges we face on Earth. These include environmental change, limited resources and a shrinking world.
As the demands of reaching and living on Mars are multifaceted, so too are the PhD topics available.
Potential topics include:
- Developing life support technologies
- Synthetic biology using extremophiles for pharma/nutraceutical production
- Methods to monitor and counter physiological and PK/PD changes in spaceflight
- Recycling of waste material for additive manufacturing
- Diagnostic assays in extreme environments
- Combating bacterial virulence and antibiotic resistance during spaceflight
Each PhD topic will involve at least two academic supervisors distributed across life sciences, physical sciences and engineering fields. You will be exposed to a broad range of activities including opportunities to interact and collaborate with the NASA Ames Research Centre and the UK Centre for Astrobiology. You may also have the opportunity to ‘fly your thesis’ via the ESA or a commercial partner.
If your degree is in a relevant life sciences or physical/engineering sciences discipline, this could be the programme for you. Applicants should also have a passion for interdisciplinary research. For more information, contact the academic lead: Professor Phil Williams, School of Pharmacy.
Understanding the brain is one of today’s biggest scientific challenges. It is not only important for basic science and health, but many researchers believe that a computational description of the brain is required to further advance artificial intelligence.
This doctoral training programme focuses on computational understanding and analysis of the brain, including how it processes information. Specific projects may involve developing computer simulations, training neural networks, developing new data analysis methods or mathematical analysis.
When you start, you’ll work with your supervisor to design a study plan based on which courses are best suited to you and your project. You will learn basic concepts in the field through tutor-guided sessions, and will also take part in a weekly journal club with fellow students to discuss internal and external research developments.
Applicants should have a background in psychology, mathematics, biology, physics, computer science or a related discipline, as well as strong quantitative skills (prior biology knowledge is not required). For more information, contact the academic lead: Mark van Rossum, School of Psychology.
Imaging technologies for vulnerable subjects
Many patients aren’t benefitting from the full power of modern medical imaging technology, either because they find the scanning environment to be too uncomfortable or because they are unable to keep sufficiently still while the image is captured.
As a result, image quality is often compromised or professionals have to change their procedures, such as sedating patients or, in the worst case, not using imaging at all. These factors particularly affect young children, people in pain, dementia patients and pregnant women, where the imaging of the foetus in utero is compromised by foetal movement.
This doctoral training programme aims to develop and make the best use of medical imaging technology to ensure access for these vulnerable subject groups. This will require a multi-disciplinary effort involving physicists, engineers, clinicians and psychologists. Through a cohort of PhD students, we will tackle some of the core problems that currently restrict patient access to imaging technology.
If you are a physicist, biomedical engineer, engineer, mathematician or computer scientist, this could be the programme for you. For more information, contact the academic lead: Professor Penny Gowland, School of Physics and Astronomy.
You can also find out more about currrent PhD projects with the Sir Peter Mansfield Imaging Centre on their website.
Low-dimensional materials and interfaces
The functional properties of materials are determined at the atomic level. They are expressed ultimately by their interactions with other components within a system from small molecules to macromolecules, cells or whole living organisms.
Developing and harnessing an understanding of these fundamental processes taking place at the nanoscale is essential for a wide spectrum of applications. These range from electronic devices, catalysts, drug delivery systems and sensors, along with materials for energy storage and conversion.
This doctoral training programme incorporates research in one of the most exciting and topical areas of science. You will be provided with a structured programme of practical and theoretical training. This is designed to develop high-level skills in innovative synthesis and advanced characterisation of new low-dimensional materials.
You will have the opportunity to undertake world-class research using the University’s unique expertise and facilities in topics that underpin the development of new innovations in advanced materials and energy technologies. For more information, contact the academic lead: Professor Neil Champness, School of Chemistry.
Mathematics and statistics for modelling and prediction
Modelling and prediction are central to application of mathematics and statistics in science and technology.
This doctoral training programme encompasses two forms of collaboration: intra-disciplinary between applied mathematics and statistics, and inter-disciplinary between mathematical sciences (such as mathematics and statistics) and researchers from a wide spectrum of other disciplines and/or with industry.
While the list of possible PhD projects/topics is very broad, the unifying theme is student training in uncertainty quantification. This emerging area is at the point of contact between applied mathematics and statistics. It focuses on modelling real-world problems under uncertainties, and is vital for situations such as:
- Informed prediction in finance, climate and engineering applications
- Reducing uncertainties, such as in high added-value manufacturing
- Better diagnoses in medicine
You will be located in the School of Mathematical Sciences and will be equipped with high-level research skills in mathematics and statistics. You will also gain valuable experience of collaborative research in another discipline.
Applicants for this programme should have a degree in mathematics, statistics or a related quantitative discipline, such as physics, engineering or computer science. For more information, contact the academic lead: Professor Andrew Wood. More information is available on the School of Mathematical Sciences website.
New generation of sustainable foods: the protein case
The sustainable supply of affordable and nutritious foods is recognised as a major global challenge.
This doctoral training programme aims to enable the development of novel, sustainable and nutritious protein foods. You will undertake multidisciplinary research with projects specialising in the interconnected areas of technological and engineering challenges, design rules and implementation of sustainable protein foods.
Design rules for the manufacture of sustainable protein foods will be developed through new knowledge. This knowledge will be created by understanding the material functionalities of protein ingredients, without purification, after exposure to typical and novel food processing regimes.
These design rules will allow the development of mechanistic models to accelerate and predict functionality of complex matrices. They will also allow the exploration of new manufacturing systems. New sustainable proteins foods must be eaten and adopted by consumers. As such, the programme will also offer projects investigating the use digital technologies to construct consumer archetypes and enable design of products for personalised experiences.
You will complete a structured programme of training to build technical and transferable/employability skills. You will have the opportunity to undertake world-class research using the University’s unique expertise and facilities as well as in an industrial setting through secondments and entrepreneurship schemes.
Applications are welcomed from candidates with relevant scientific background in chemistry, food chemistry, food sciences, physical chemistry or chemical engineering; you should also have a passion for interdisciplinary research. For more information, contact the academic lead: Joanne Gould, School of Biosciences.
Fully funded studentships are available for UK applicants. EU applicants who are able to confirm that they have been resident in the UK for at least three years before October 2019 may also be eligible for a full award. EU students who are not able to prove that they meet the residency criteria may apply for a fees only award.
All candidates should have, or expect to obtain, a First or 2:1 in a relevant discipline. Specific subject areas are specified above.
Successful applicants will receive a stipend (£15,009 per annum for 2019/20) for up to three-and-a-half years, tuition fees and a Research Training Support Grant.