Chemical Engineering

Whether it is the substantial cooling requirements of future data centres or energy-dense batteries for next-generation electric vehicles, the need for energy-efficient electronics cooling systems is ubiquitous. This is because while recent developments have produced ever-smaller and ever-denser devices, heat fluxes comparable to the surface of the Sun can be generated at hot spots, producing high temperatures that adversely impact their performance and raise risk of catastrophic failure. In the last decade and a half, novel 2D nanomaterials have been developed with unique thermal properties (e.g. ultrahigh thermal conductivity). These nanomaterials can be used to form surface coatings to enhance heat transfer from the extremely hot surfaces of electronic devices into the adjacent coolant liquid. 

However, our understanding of thermal transport at this nanomaterial/liquid interface is currently limited. For 2D nanocoatings, the nanomaterial can be either carbon-based (graphene nanoparticles or nanoflakes, nanopores, graphene oxide nanosheets etc), boron-based (boron nitride nanosheets, nanotubes, etc) or hybrid (e.g. boron carbon nitride). Similarly, while water is the most studied coolant liquid, realistic applications involve dielectric fluids (e.g. benzene, pentane). Molecular dynamics (MD) simulations represent a powerful tool to study such interfaces, but MD of nanomaterial/liquid interfaces require well-calibrated intermolecular potentials, which don’t currently exist. This project will rely on recent advances in neural networks to develop machine learning potentials (MLPs) for MD simulations of realistic nanomaterial/coolant-liquids and use these to gain fundamental insights into interfacial thermal transport. The goals are to:

1) run ab-initio molecular simulations to sample relevant nanomaterial/liquid interfaces.

2) construct new MLPs by using generated data from 1) and validate them.

3) use MLPs to run classical MD simulations and characterise thermal transport.

This PhD project will be based within the School of Engineering, University of Edinburgh. This PhD project will be supervised by Dr Rohit Pillai and Dr Eleonora Ricci, and the successful applicant will join an active, friendly, and collaborative research group (see https://multiscaleflowx.github.io/). Our group makes extensive use of ARCHER2 – the UK’s national supercomputer, which is based in Edinburgh. This PhD will give the successful applicant the skills and experience to become a future leader in either academia or industry. The supervisors will provide the successful applicant with exceptional research and training opportunities, including:

• regular weekly meetings to discuss the research progress.

• opportunities for travel to participate in workshops/summer schools dedicated to advanced computational methods, as well as present results in international conferences.

• training and experience in state-of-the-art engineering research.

• mentoring from other investigators and experienced postdoctoral researchers.

• exceptional career development opportunities with strong institutional support of early career researchers.

Minimum entry qualification - an Honours degree at 2:1 or above (or International equivalent) in a relevant science or engineering discipline, possibly supported by an MSc Degree. Further information on English language requirements for EU/Overseas applicants.

Tuition fees + stipend are available for Home/EU and International students

Further information and other funding options.

Developing renewable energy solutions that can be rapidly implemented in the market using eco-friendly materials and manufacturing methods is crucial. Among various renewable technologies, photovoltaics have significant potential to support climate change mitigation. Organic photovoltaics (OPVs) have recently attracted considerable attention due to a new family of semiconductors that enable highly efficient light harvesting in both indoor and outdoor environments. Additionally, OPVs offer a low carbon footprint and high recyclability potential.

However, a current limitation is the use of toxic solvents and materials in manufacturing. Most organic electronic devices require halogenated and non-halogenated aromatic solvents, which are often carcinogenic or toxic to human reproductive systems and harm the environment. For large-scale production and commercialization, this is a critical issue.

This project aims to enhance the performance of OPVs through engineering strategies, eliminate the use of toxic materials and implement methods to enhance their stability. In addition, thin films and OPVs will be evaluated with a series of optoelectronic and morphological characterisation tools.

The PhD candidate will be supervised by Dr Julianna Panidi (School of Engineering) and Dr Yue Hu (School of Chemistry).

The successful candidates will join our team, which includes researchers from the Centre for Electronics Frontiers, the Institute for Integrated Micro and Nano Systems, the School of Chemistry, and the wider College of Science and Engineering.

Before you apply: We strongly recommend that you contact the supervisor for this project before you apply.

Minimum entry qualification - an Honours degree at 2:1 or above (or International equivalent) in a relevant science or engineering discipline, possibly supported by an MSc Degree. Further information on English language requirements for EU/Overseas applicants.

Tuition fees + stipend are available for Home/EU and International students

Further information and other funding options.

The use of lipid nanoparticles (LNPs) as delivery systems has revolutionized biomedical applications, particularly in immunotherapy. LNPs can encapsulate and deliver therapeutic agents such as nucleic acids, proteins, and small molecules, enabling targeted treatment of diseases including cancer, autoimmune disorders, and infectious diseases. This PhD project, based at the forefront of immunotherapy research, aims to develop and optimize lipid nanoparticles to enhance their effectiveness as carriers for immunotherapeutic agents, improving immune responses and treatment outcomes.

The key objectives of this research include:

1. Designing and Engineering Lipid Nanoparticles: You will develop innovative strategies to engineer lipid nanoparticles with improved stability, biocompatibility, and enhanced delivery capabilities. This includes optimizing the lipid composition, particle size, and surface properties to achieve optimal cellular uptake and targeted delivery to immune cells.
2. Encapsulation of Immunotherapeutic Agents: The project will focus on formulating lipid nanoparticles for the encapsulation and controlled release of immunotherapeutic agents such as mRNA vaccines, cytokines, and immune modulators. You will explore novel methods for improving the loading efficiency and bioactivity of these agents.
3. Evaluating Immune Response and Efficacy: The candidate will conduct preclinical studies to evaluate the immunomodulatory effects of the lipid nanoparticle formulations, assessing their ability to activate immune cells, stimulate desired immune responses, and enhance the therapeutic efficacy of the treatment in various disease models.
4. In Vitro and In Vivo Evaluation: You will assess the safety, stability, and pharmacokinetics of the lipid nanoparticles in both in vitro cell culture systems and in vivo animal models. A focus will be placed on the nanoparticles' ability to trigger potent immune responses without causing adverse side effects.

We are seeking a highly motivated PhD candidate with a background in pharmaceutical sciences, nanotechnology, chemical engineering, or related fields. Experience in nanoparticle formulation, drug delivery systems, or immunology is highly desirable. The ideal candidate will be driven to advance immunotherapy technologies with the potential to make a significant impact on cancer treatment and beyond. Other types of nanoparticles may be considered as well if with unique advantages.

Join us at the cutting edge of immunotherapy research and contribute to the development of next-generation therapeutic systems with transformative potential.

Applications are welcomed from self-funded students, or students who are applying for scholarships from the University of Edinburgh or elsewhere

Further information and other funding options.

Microfluidic devices are transforming the landscape of disease diagnosis by offering high sensitivity and rapid results. These devices hold immense potential for a wide range of applications, including the swift identification of bacterial infections in patients' biological samples. The ability to quickly detect pathogens allows doctors to prescribe the appropriate antibiotics at the right time, improving treatment outcomes and helping combat the growing problem of antibiotic overuse. Another exciting area of microfluidics is the use of organ-on-a-chip designs, which can revolutionize cancer diagnosis by enabling more precise and personalized medical assessments.

This groundbreaking project, led by the Institute for Bioengineering at the University of Edinburgh, aims to develop innovative microfluidic platforms that enable efficient, rapid, and accurate diagnostics. The research will also explore the integration of Artificial Intelligence (AI) to optimize the design of microfluidic devices, enhancing their performance and streamlining the diagnostic process. By combining cutting-edge technology with advanced materials science, the project will push the boundaries of medical diagnostics and help shape the future of healthcare.

We are now seeking a highly motivated and talented candidate to undertake this exciting research as part of a dynamic team. The ideal PhD candidate will have a strong background in chemical engineering, materials science, biology, or related fields, with hands-on experience in one or more of these areas. A passion for interdisciplinary research, problem-solving, and innovation is essential, as this project offers the opportunity to make a significant impact on the future of disease diagnostics and healthcare.

If you are driven by curiosity and eager to contribute to pioneering research, we invite you to apply for this PhD opportunity. Join us in advancing the field of microfluidic diagnostics and help us tackle some of the most pressing challenges in modern medicine.

Entry requirement: minimum entry qualification – an Honours degree at 2:1 or above (or international equivalent) in chemical engineering, chemistry, materials science, biomedical engineering, or cell biology. 

Further information on English language requirements for EU/Overseas applicants.

Applications are welcomed from self-funded students, or students who are applying for scholarships from the University of Edinburgh or elsewhere

Further information and other funding options.