About
There are a great range of PhD research opportunities at the AiPT. You could be working on optical communications, sensing, biomedical photonics, laser material processing, nanoscale photonics, nonlinear fibre lasers, ML and unconventional computing. There are a number of projects that have guaranteed funding that have deadlines (see here). We also have a full list of all projects below, broken down by research theme, that you can look through (see here).
Fully Funded Opportunities
Neuromorphic cameras for object detection and image enhancement, focusing on high-speed sensing and improved imaging
Supervisor: David Benton d.benton@aston.ac.uk
About the Project: Event cameras (also known an neuromorphic cameras are a recent development that detect changes in intensity and can be used to sense movement or variation in the scene. They only output events for pixels that have changed unlike standard frame-based cameras and can provide much higher rate of information output than conventional camera and they have higher dynamic range. They provide the potential for novel sensing and detection channels to complement existing imaging methods. The full benefits of this technology are yet to be realised in industry, but these sensors are likely to have utility across a number of applications including the quantification and correction of atmospheric turbulence, stabilisation of images from a moving vehicle, the de-blurring of motion-related effects, object detection in obscuring environments, the detection of laser illumination, fast object tracking and surveillance detection. It is also likely that data fusion of their output with conventional cameras, perhaps working in other but complementary wavebands, will unlock enhanced sensing capabilities.
This PhD project will explore these applications by building a foundational understanding of their operating principles. This will be achieved through a programme of experimentation and modelling, focussing on the most promising areas with maximum utility.
This research opportunity is based at the Aston Institute of Photonic Technologies (AIPT) at Aston University and is sponsored by Thales UK. The project is based at Aston University in Birmingham and will also include a three-month secondment to work with Thales experts in Glasgow.
Person Specification: The successful applicant should have been awarded, or expect to achieve, a Masters degree in a relevant subject with a 60% or higher weighted average, and/or a First or Upper Second Class Honours degree (or an equivalent qualification from an overseas institution) in a relevant subject. Preferred skill requirements include knowledge/experience of programming and/or modelling skills, an aptitude for experimental work, and an interest in cameras, imagery and optical sensors .
Contact: David Benton (d.benton@aston.ac.uk) for more details.
Distributed Foundation Model Training over Geo-Distributed Optical Networks
Supervisor: Pedro Freire freiredp@aston.ac.uk
About the Project- Join a groundbreaking research project that aims to revolutionize how we train the next generation of AI foundation models. This industrially-funded PhD, in partnership with Corning – the world’s largest optical fibre provider – addresses one of the most pressing challenges in modern AI: the computational demands of training large language models such as GPT-5 and Llama 4.
Current approaches require tens of thousands of GPUs in centralized clusters with ultra-low-latency interconnects, a solution that is cost-prohibitive, scarce, and inflexible. This project will investigate a paradigm-shifting alternative: distributed model training over geo-distributed optical networks. The successful candidate will have a good mathematical background and knowledge in the areas of machine learning, numerical modelling, optical communications.
Applicants must have Master’s degree (or equivalent) in Computer Science, Electrical Engineering, Telecommunications, or related field. Experience in Machine Learning foundation, Excellent programming skills such as Python, C++ or similar and familiarity with modern data centre architectures will be an add on.
What We Offer-
· Full financial support: Competitive stipend covering tuition fees and living expenses.
· Industry exposure: Regular collaboration with Corning’s research teams and access to their facilities
· Professional development: Opportunities to present at top-tier conferences and publish in leading journals
· Career prospects: Strong pathway to careers in industry research, academia, or tech leadership roles
· Cutting-edge facilities: Access to world-class optical and computing laboratories
Application Process
At this Expression of Interest stage, please submit:
1. Detailed CV including academic achievements, relevant experience, and technical skills.
2. Academic transcripts from your undergraduate and postgraduate studies.
3. Two academic references (contact details for referees who can speak to your research potential).
Next steps: Shortlisted candidates will be invited to an interview with Aston and Corning representatives (online or in person) to discuss their background, motivation, and relevant expertise.
Deadline of Expression of Interest: 30 November 2025 Start Date: January 2026 or March 2026 (depending on circumstance Contact for CVs and informal discussion: freiredp@aston.ac.uk)
Potential Opportunities
There will be funding on these jobs for the right candidate. If you see something you like, then contact the Supervisor to discuss your options. There is no deadline, positions are available until the relevant candidate will be found. Contact Natalia Manuilovich (n.manuilovich@aston.ac.uk) with any other queries.
Tuition fees: PAID [1]
Full home/overseas tuition fees paid for 3 year
Maintenance: PAID [1]
Annual £18,622 (2024/25 full time equivalent)
[1] allocated in competitive process.
Optical Communications
Multi-Band Amplification and Transmission for Energy-Efficient Optical Networks
Supervisor: Dr Aleksandr Donodin a.donodin@aston.ac.uk
Multi-Band Amplification and Transmission for Energy-Efficient Optical Networks
Global demand for data is growing at an unprecedented rate, driven by AI, cloud services, and next-generation digital infrastructure. Today’s optical networks, limited to C+L bands, cannot meet future capacity and power-efficiency requirements. Expanding into multi-band transmission — across O, E, S, C, L and U bands — together with new amplifier technologies, is essential for sustainable network growth.
This project will explore novel fibre amplifiers, including bismuth-doped fibre amplifiers (BDFAs) and hybrid solutions, alongside advanced multi-band transmission experiments. A central focus will be energy efficiency, developing amplifier and system designs that reduce power consumption while delivering high-capacity, low-noise performance for data-centre interconnects and regional networks.
You will gain experience in amplifier design and characterisation, high-capacity transmission testbeds, and system modelling, while contributing to greener, more sustainable photonic technologies.
Collaboration opportunities with Lightera, Coherent, KDDI Research, NICT, Fraunhofer HHI, Pilot Photonics, and Enlightra will connect your research directly to cutting-edge devices and global system demonstrations. Possible short secondments to aforementioned companies are available.
Contact: Dr Aleksandr Donodin (a.donodin@aston.ac.uk) for more details.
Optically Enhanced Transponders for Digital Futures
Supervisor: Prof Andrew Ellis andrew.ellis@aston.ac.uk
Communication networks are now deeply into the predicted capacity crunch, with research attention focussed on achieving massive parallelism (wavelength and spatial multiplexing) and systems operating close to the signal to noise ratio of analogue to digital converters. To fully exploit the characteristics of such systems, using multiple-input multiple-output technology, and maintain cost per bit reductions will require advanced media converters to access bandwidths and digital resolutions (effective number of bits) beyond the scope of conventional electronics. Using optical frequency combs and optical interferometers, implemented integrated photonics, this project will develop advanced media converters for wide range of conventional optical communication applications, including long haul and access networks, data centres and free space communications, in addition to novel spatially multiplexed networks where enhanced super-linear performance will be demonstrated. On completion of their PhD the successful applicant will be an expert in outsourced opto-electronic component manufacture and optical communication systems.
Applicants should have been awarded, or expect to achieve, a First Class Honours degree (or equivalent from an overseas institution), in Physics or Electronic Engineering, or a Masters degree with Distinction in a subject related to optical communication. Preferred skill requirements include practical experience of optical communications or integrated photonics.
Contact: Prof Andrew Ellis (andrew.ellis@aston.ac.uk) for more details.
Bismuth-doped fibre amplifiers and their applications in wideband networks
Supervisor: Prof Sergei K. Turitsyn s.k.turitsyn@aston.ac.uk
Project Summary Aim and Objectives:
a. The project will be devoted to the experimental and numerical investigation of the different designs of O-band bismuth-doped fibre amplifiers and their implementation in wide-band optical networks. In addition, the successful candidate will develop novel methods of machine-learning algorithms for amplifier modelling and transmission line optimisation.
b. The optical fibre communications research group at AiPT has a long history of innovations in optical amplification and applied machine learning. The successful applicant will join a research team comprising Prof Sergei Turitsyn, Prof Wladek Forysiak, and Dr Aleksandr Donodin and will be provided with a state-of-the-art facility including 100Gb/s optical transmission test-beds, automatic amplifier testing setup, high speed electronic test equipment, dedicated computational facilities, and bismuth-doped fibres for O-band amplification.
Knowledge and skills required in applicant:
The successful applicants should have been awarded, or expect to achieve, a Master’s degree in a relevant subject with a 60% or higher weighted average, and/or a First or Upper Second Class Honours degree (or an equivalent qualification from an overseas institution) in physics, applied physics, or electronic/electrical engineering. Preferred skill requirements include knowledge/experience of optical fibre communications, optical amplifiers, photonics, and/or mathematical modelling of physical systems, including digital signal processing and machine learning.
Contact: Prof Sergei Turitsyn (s.k.turitsyn@aston.ac.uk), Dr Ian Phillips (i.phillips@aston.ac.uk), Dr Aleksander Donodin(a.donodin@aston.ac.uk) or Prof Wladek Forysiak (w.forysiak@aston.ac.uk) for more details.
High capacity optical transponders for next generation communication systems
Supervisor: Dr Stylianos Sygletos s.sygletos@aston.ac.uk
Area of research: Optical Communications, Photonic Devices
Optical communications have been a cornerstone of our information-based society. To keep up with their role, they must continue serving an exponentially increasing traffic demand while preventing a comparable growth in energy consumption. This requires new transponder technologies characterized by an enhanced operational bandwidth, low power consumption and the ability to deal with signals of high spectral efficiency. The proposed PhD project aims to redesign the architecture of future optical transponders by exploiting the photonics to:
1. Develop power-efficient all-optical schemes for analogue-to-digital (ADC) and digital-to-analogue (DAC) conversion in the transceiver hardware to enable high-capacity transmission/detection of telecommunication signals.
2. To enhance the performance of the existing electronic DAC/ADC circuits through pioneering analogue signal processing and time bandwidth engineering in the optical domain.
3.To evaluate the performance of the developed schemes in various transmission scenarios, targeting world-record results in terms of transmitted spectral efficiency and data rate.
The applicant needs to have a strong background in optical communications and the waveguide theory of photonic devices. Strong mathematical modelling skills of photonic components and telecommunication systems, e.g. using Matlab/Python will be needed. Prior experience in the design of photonic components using the Lumerical Suite will also be appreciated.
Contact: Dr Stylianos Sygletos (s.sygletos@aston.ac.uk) for more details.
All-optical frequency conversion
Supervisor: Dr Vladimir Gordienko v.gordienko1@aston.ac.uk
Area of research: Four-wave mixing, Optical Communications
All-optical frequency conversion is a powerful technique of transferring optical signals or optical power between frequencies of choice. All-optical frequency conversion based on four-wave mixing in optical fibres allows for generation of optical signals and optical waves at frequencies lacking suitable sources with tuneability across a very broad range of tens of THz. Additionally, all-optical frequency conversion facilitates a transparent and flexible translation of optical signal channels between frequencies of choice in optical networks to improve their capacity and robustness.
The project will combine recent technology advances in all-optical frequency conversion with novel ideas to realize the potential of this technology for modern optical communications. The project will focus on experimental work in our well-equipped labs stocked with all required components and instruments. The student will be working in a team with Dr Vladimir Gordienko, Prof Nick Doran and Prof Andrew Ellis having a deep theoretical and experimental expertise in nonlinear fibre optics and optical communications. A successful applicant will have an experience of work in an optical lab and a background knowledge of nonlinear optics.
Contact: Dr Vladimir Gordienko (v.gordienko1@aston.ac.uk) for more details.
Ultra-Fast Data Transmission in Free-Space Optical Communications
Supervisor: Prof Andrew Ellis andrew.ellis@aston.ac.uk
Area of Research: Digital Communications, Digital Signal Processing, Digital Image Processing, Optics
In this project, we will employ mode-division multiplexing (MDM) multiple-input multiple-output (MIMO) technologies to enable record-high multiple Terabit transmission in the communication systems, allowing ultra-fast satellite communications and Ground-to-Ground wireless communications. This project will be supported by the Aston Institute of Photonic Technologies, a world-leading optical communication laboratory, which provides cutting-edge experimental instruments, computation resources, and office resources. The successful applicant will also have a good chance of secondment to world-leading research institutes such as Nokia Bell Labs. After the PhD research, we anticipate the student to have a strong and comprehensive knowledge of cutting-edge experimental communication systems, including digital signal processing, channel modelling, digital image processing, and even physical optics, allowing him/her to be a strong candidate in both academia and industry in his/her future careers.
We anticipate the candidate to have a strong knowledge of electrical engineering, especially in digital communications and digital signal processing. It is also preferable that the students have a good knowledge of digital signal processing and optics. The experience of writing journal papers will be also preferred.
Contact: Prof Andrew Ellis (andrew.ellis@aston.ac.uk) for more details.
Machine learning for optical communications and sensing
Supervisor: Prof Sergei K. Turitsyn s.k.turitsyn@aston.ac.uk
This PhD project is at the interface of the data science, machine learning, nonlinear science, digital signal processing and optical communications. The exponential surge in the global data traffic driven by the skyrocketing proliferation of different bandwidth-hungry on-line services and various broadband services, brings about the escalating pressure on the modern optical communication systems. Nonlinear properties make optical fibre channels considerably different from wireless and other traditional linear communications channels. There is a clear need for development of radically different methods for coding, transmission, and (pre & post) processing of information to mitigate nonlinearities.
The successful candidate will work on developing and optimising various designs of deep machine learning-based devises (autonomous agents) and systems (both physics-inspired and black-box solutions) aiming at recovering the information transmitted over the optical channel, to achieve the best performance in terms of processing quality, complexity, and device’s memory requirements. It is planned that the study will cover versatile designs of deep neural networks, ranging from multilayer perceptrons to transformers and variational autoencoders. The new system designs will be studied, first, theoretically, and validated and investigated experimentally.
From the industry perspectives, design of practical and implementable processing algorithms requires knowledge of ASICs and real-world conditions and restrictions. The project is aimed at the development of novel practically implementable disruptive techniques for fibre-optic communications.
Contact: Prof Sergei K. Turitsyn (s.k.turitsyn@aston.ac.uk) for more details.
Optical Sensing
Trans-oceanic distributed sensing
Supervisor: Prof David Webb d.j.webb@aston.ac.uk
Project Summary: The world’s seas and oceans are criss-crossed with optical fibre telecommunications cables, forming the backbone of the internet. This project aims to investigate approaches that would allow this infrastructure to be used as a sensing network, to monitor for seismic activity and provide early warning of Tsunamis, as well as to warn against imminent damage to communications cables. Damage can potentially occur by accident, due to the anchors of ships dragging over the cable, but increasingly telecommunications cables are seen as major items of infrastructure that at times of conflict can be intentionally compromised by a hostile agent.
There are significant challenges in sensing over distances that can be as much as 10,000 km. We aim to explore a range of interferometric approaches to distributed optical fibre sensing and couple this with the latest data analytical and machine learning approaches to event recognition at low signal to noise ratio.
There is commercial interest in this work and a secondment to industry may be available to the right candidate.
Knowledge and skills required in applicant: The successful applicants should have been awarded, or expect to achieve, a Master’s degree in a relevant subject with a 60% or higher weighted average, and/or a First or Upper Second Class Honours degree (or an equivalent qualification from an overseas institution) in physics, applied physics, or electronic/electrical engineering. Preferred skill requirements include knowledge/experience of optical fibre sensing and related electronic signal processing and some experience of data analytics and/or machine learning.
Contact: Prof David Webb (d.webb@aston.ac.uk), Prof Sergei Turitsyn (s.k.turitsyn@aston.ac.uk) or Dr Kaiming Zhou (k.zhou@aston.ac.uk) for more details.
Opto-electronic integrated systems to transform infrastructure performance
Supervisor: Dr Haris Alexakis c.alexakis@aston.ac.uk
The building and construction sector accounts for 39% of global CO2 emissions, with 11% corresponding to construction materials manufacturing. Hence, achieving climate neutrality requires radical reduction of material and energy use in construction, while improving maintenance and longevity of existing structures.
NOESIS (Novel Opto-Electronic Systems for Infrastructure Sustainability) is a new interdisciplinary group within AIPT with the aim to address the challenges to digitally transform the built environment through smarter information. The successful candidate will engage in research that converges photonics, electronics, data science, systems and civil engineering for real world applications, in collaboration with world-leading groups on structural health monitoring, infrastructure managers, and technology and engineering firms.
The candidate will work within the dynamic interdisciplinary environment of NOESIS to deliver actionable information for optimum performance and maintenance of civil infrastructure by conducting research in one (or more) of the following themes: (i) R&D of novel laser-based (distant) and fibre-optic-based infrastructure sensing, (ii) data fusion for enhanced prognosis and diagnosis, and (iii) ‘edge’ computing and integrated systems.
Prior experience on structural health monitoring, optical/electronic sensing, signal processing, statistical modelling or systems integration is desirable.
Contact: Dr Haris Alexakis (c.alexakis@aston.ac.uk) or Prof David Webb (d.webb@aston.ac.uk) for more details.
Machine learning and advanced signal processing for optical sensing of civil engineering infrastructure
Supervisor: Prof David Webb d.j.webb@aston.ac.uk
Machine learning is having a rapidly increasing impact on many aspects or our daily lives, ranging from AI based medical diagnosis and autonomous vehicles to its more mundane use on consumer platforms, suggesting things we might like to buy or listen to. Machine learning and data analytic techniques have the potential to revolutionise how we sense things and how we turn the raw data from measurements into useful information.
The successful candidate will research into the use of machine learning – including probabilistic approaches – to optimise the signal to noise ratio in optical sensing systems of various types including those based on interferometry, fibre grating based sensors and spectroscopy. A second aspect of the research is the extraction of useful information from large measurement datasets. This research is quite generic in nature but we do have a particular interest in applications in the aerospace sector.
The ideal candidate will be interested to undertake research that contains a balance between theory/simulation and experimental verification.
Contact: Prof David Webb (d.webb@aston.ac.uk) for more details.
Mid-infrared fibre device, sensor and sensing technology
Supervisor: Dr Kaiming Zhou k.zhou@aston.ac.uk
Area of research: ultrafast laser microfabrication, fibre optical device, gas sensing , mid infrared , laser spectroscopy
Many applications require fast and precise spatial distribution determination of targeted substances. In partnership with a leading food/agri-tech company, this project combines three advanced technologies of AIPT: distributed/discrete fibre optical sensing, mid infrared fibre laser spectroscopy and machine learning for sensitive 3D chemical mapping in real time. These fields have seen remarkable advances in recent years. Fibre optical sensing is used for structure health monitoring in aerospace, civil engineering and geographic monitoring. Mid infrared is the spectral fingerprint region of many substances found in life sciences, and industries including food and agriculture, pharmaceuticals and chemistry processing. Machine learning, an artificial intelligence technology, finds a long list of applications including medicine, IT, telecommunications agriculture, computer vision. Aligning with AIPT’s on-going focus with food and agriculture technologies and combining these technologies, this project will advance research covering laser microfabrication, mid infrared fibre laser, signal processing and data interpretation for 3D biochemical sensing.
Contact: Dr Kaiming Zhou (k.zhou@aston.ac.uk) for more details.
Advanced Grating and Fabrication Technologies
Supervisor: Dr Kaiming Zhou k.zhou@aston.ac.uk
Fibre Bragg gratings (FBGs) are essential optical components widely used in applications such as sensing, fibre lasers, and optical communications. While standard uniform gratings are suitable for many purposes, advanced applications often require more sophisticated grating structures. These include features such as apodisation, chirp, ultra-narrow or ultra-wide bandwidth, ultra-weak reflectivity, grating arrays, and ultra-long gratings. Achieving these advanced characteristics demands innovative designs and state-of-the-art fabrication techniques.
This project aims to develop advanced fabrication technologies for next-generation fibre Bragg gratings, with a particular focus on ultra-long gratings. The work will leverage high-precision equipment, including our existing long-translation bearing stage, to push the boundaries of grating performance and versatility.
The project is highly interdisciplinary, gaining the candidate integrated expertise in electronics, process control, signal processing , software programming, mechanics, laser microfabrication, photonic device engineering, and modelling. It offers a unique opportunity for a highly motivated candidate to develop hands-on skills and build substantial research capacity in a cutting-edge field.
The successful candidate will be supervised by Dr. Kaiming Zhou, Dr. Adenowo Gbadebo, and Prof. Sergei Turitsyn. Applicants should hold (or expect to obtain) a degree equivalent to an MSc in electronics, physics, or a closely related discipline.
Contact: Dr Kaiming Zhou (k.zhou@aston.ac.uk) for more details.
Optical gas sensing
Supervisor: Prof David Webb d.webb@aston.ac.uk
Contact: Prof David Webb (d.j.webb@aston.ac.uk) or Prof Sergei K. Turitsyn (s.k.turitsyn@aston.ac.uk) for more details.
Polarimetric shape sensing
Supervisor: Dr Sergey Sergeyev s.sergeyev@aston.ac.uk
Project Summary, Aim and Objectives:
Shape sensing technology is of great practical significance in the real-time monitoring of structural integrity of engineering structures (buildings, bridges, wind power stations, aircrafts), or 3D shape and position in the context of human motion, robotics, and surgery instruments. By supporting a high measurement resolution, providing resistance to harsh environments and corrosion, enabling an array of sensors within a single fibre with a very small diameter, fibre optic shape sensors (FOSSs) are particularly attractive and competitive because they can be embedded into devices, instruments, or structures. So, FOSSs offer an extremely valid alternative to traditional methods, allowing the shape to be tracked continuously and dynamically without the need for visual contact. One of the major shapes sensing related problems is monitoring barely visible impact damage (BVID) in carbon fibre reinforced polymer (CFRP) composite laminates which is of great importance in the context of inflight monitoring structural integrity of aerospace structures. Though FOSS technologies can provide information on the localisation of the structural defects based on the shape reconstruction, there is still a lack of technologies for high-resolution localisation, identification of defects, and prediction of their evolution. The suggested research aims to develop the cost-effective technique for monitoring BVID in CFRP laminates based on analysing the fundamental property of light reflected from FOSSs, e. g. states of polarisation, and combines fibre optics, laser physics, nonlinear science and signal processing disciplines. The suggested technology enables transforming localised small changes in the structure shape into the dynamic polarimetric signatures (caused by FOSS’s stretch, twist and bend) as a function of the damage mode, rate, and level. Using polarimetric data-driven Artificial Neural Network, we will enable localisation and identification of the structural defects and evolve towards supporting data-driven structural performance assessment and optimised decision-making.
Knowledge and skills required in applicant:
A First class or upper second degree in Electronic Engineering, Applied Physics or equivalent is required.
To apply for the above projects, please contact Principle Investigators stated in the description of the project and visit the ASTON WEBSITE for more details on application.
Contact: Dr Sergey Sergeyev (s.sergeyev@aston.ac.uk) or Dr Hani Kbashi (h.kbashi@aston.ac.uk) for more details.
Photon sensitive laser detection
Supervisor: Prof David Benton d.benton@aston.ac.uk
Detecting lasers through their coherence properties rather than their brightness characteristics, is a beneficial approach to the problem of identifying when you are being illuminated. This is an important issue because laser radiation does not appear naturally and hence if you see one, you should probably want to know why it is there. This concept has been pioneered by David Benton at Aston University who has demonstrated that this technique is both cost effective and sensitive. The next leap for this technology involves taking detection to the ultimate limit and detecting coherence properties one photon at a time. This project will involve building the most sensitive laser detector on the planet using single photon detectors. This has a number of applications with the most intriguing being the idea of detecting extra-terrestrial laser radiation and all that would imply.
The student will be working with David Benton and Richard Nock to demonstrate and develop this ground breaking technology. The student will require a physics degree with skills in electronics and programming as well as familiarity with optical equipment. Support and interest will be provided by government agencies and commercial partners.
Contact: Prof David Benton (d.benton@aston.ac.uk) for more details.
Laser Material Processing
Development of sapphire based optical fibre sensors for extreme condition monitoring
Supervisor: Prof Kate Sugden k.sugden@aston.ac.uk
Area of Research: Photonics, Materials, Sensors, Spectroscopy, Devices
Condition monitoring in harsh environments such as at high temperatures, pressures or corrosive liquids is critically important for improving efficiency and prolong machinery lifetime. These environments can easily damage electronic based sensor circuitry. Aston University has an established track record on fibre optical sensor and sensing technologies which have been used in civil engineering , aerospace, oil, biochemistry etc. In partnership with a leading optical fibre company, this project seeks to overcome limitations of common glass optical fibre including low resistance to corrosive liquids such as hydrofluoric acid and relatively low melting point by exploring the development of a new class of fibre optical sensors made from sapphire. The properties of sapphire make it attractive for harsh environments monitoring but these properties present challenges related to processing and sensor fabrication. This project will develop the fabrication of sensors composed from this material and its practical use in harsh environments.
Contact: Dr Kaiming Zhou (k.zhou@aston.ac.uk) or Prof Kate Sugden (k.sugden@aston.ac.uk) for more details.
Nanophononics
Picometre Surface Nanoscale Axial Photonics
Supervisor: Prof Misha Sumetsky m.sumetsky@aston.ac.uk
It has recently been recognised that the fabrication of a range of emerging photonic microdevices promising to revolutionise computer, communication, and sensing technologies must be performed with unprecedented picometre (one-hundredth of the atomic size) precision.
The successful candidate for this PhD position will be involved in the experimental and theoretical development of a new technology called Surface Nanoscale Axial Photonics (SNAP), which will enable this astonishing picometre fabrication precision.
Further aims of the project include:
·Theoretical modelling of nanoscale effects and processes in SNAP
·Development of experimental methods of picometre-precise fabrication of miniature optical devices at the surface of an optical fibre
Person Specification
The successful applicant should have been awarded, or expect to achieve, a Masters degree in a relevant subject with a 60% or higher weighted average, and/or a First or Upper Second Class Honours degree (or an equivalent qualification from an overseas institution) in a relevant subject. Preferred skill requirements include:
· Strong analytical and numerical calculation skills and mathematical modelling skills
· Strong skills in solid state physics and quantum mechanics
· Experience in theoretical modelling and experimental investigation of optical devices including optical microresonators
Contact: Prof Misha Sumetsky (m.sumetsky@aston.ac.uk) for more details.
Biocompatible microelectrode arrays for electrophysiological brain recordings
Supervisor: Dr Petro Lutsyk p.lutsyk@aston.ac.uk
Area of Research: Nanotechnology, microelectrode arrays, ink-jet printing, electrophysiology
The motivation for the proposed research stemmed from the fact that there is currently a gap and developmental opportunities in the technology of biocompatible microelectrode arrays (MEAs) for the electrophysiological study of brain pathologies, in particular epilepsy. The project goal is to overcome the limitations of current MEAs restricting the supply of O2/CO2 to the interface of studied tissue and the arrays and to open novel avenues for a dramatic change in brain signal recording. A new design using nanotechnology can ensure the brain tissue does not become anoxic in a couple of hours and can be studied for a long time providing ground-breaking opportunities for brain electrophysiology. To this end, the following Research Objectives (ROs) will be pursued:
• RO1: To develop & optimise nanofabrication protocol for biocompatible MEA using inkjet printing technology & deploying MEAs to investigate its biocompatibility.
• RO2: To validate innovative MEA in electrophysiological studies of brain tissues.
The successful applicant should have a first-class or upper second-class honours degree or equivalent qualification in Physics, Engineering, Nanoscience, or similar. Preferred skill requirements include knowledge/experience of nanomaterials processing, experimental characterisation of liquid/solid samples by electrical measurements, and optical spectroscopy techniques.
Contact: Dr Petro Lutsyk (p.lutsyk@aston.ac.uk) for more details.
Optical spectroscopy for agricultural and food samples monitoring
Supervisor: Dr Alex Rozhin a.rozhin@aston.ac.uk
Project Summary, Aim and Objectives:
Household and industrial food waste pose significant environmental challenges, prompting a critical need for advanced sensor systems in the food and agricultural industries. This issue is not just about the environment; it holds substantial economic and social importance. Foods face contamination from various sources such as fertilizers, micro/nano-plastics, and bacterial agents. The composition of plant and animal products is complexly linked to the soil’s biochemistry, further complicating quality control.
The current methods employed by the food industry are outdated, relying on 19th-century techniques, primarily long-term bacterial analysis in Petri dishes. These methods demand high precision, expensive equipment, and a workforce with advanced qualifications, making them financially burdensome, particularly for small-scale producers and retailers.
Optical spectroscopy emerges as a promising solution for the food and agricultural sectors. This technology allows the testing of samples in both liquid and solid forms, offering insights into chemical and bacterial pollution, as well as the biological components of plant and animal products.
Aim:
This project aims to revolutionise food quality control by exploiting the potential of optical spectroscopy. We seek to develop efficient sampling protocols and create a user-friendly USB-based spectrometer for quick food analysis. Our ultimate goal is to establish a library of various food fluorophores, accessible to scientists, small and medium enterprises (SMEs), and the public. This library will enable comparisons between express spectroscopic data and a high-performance library, facilitating the training of a food control system to determine contaminants, bacteria, and other factors.
Objectives:
Develop efficient sampling protocols for characterising food samples using high-performance UV-NIR and photoluminescence spectrometers.
Construct a USB-based spectrometer for express analysis of food samples, fostering a simple and accessible approach to quality assessment.
By achieving these objectives, we aim to bring about a transformative shift in how we monitor and ensure the quality of food products.
Knowledge and skills required in applicant:
A PhD candidate with expertise in soft material Photo-Physics or Photo-Chemistry, skilled at using UV-NIR absorption/transmission and photoluminescence excitation-emission spectrometers. Familiarity with advanced spectroscopic data processing techniques, like Parallel Factor Analysis, is vital. Proficient in essential chemical processes such as mixing, filtration, and centrifugation.
Contact: Dr Alex Rozhin (a.rozhin@aston.ac.uk) or Dr Petro Lutsyk (p.lutsyk@aston.ac.uk) for more details.
Nonlinear Photonics and Fibre Lasers
Topic
To be announced
To be announced shortly
The Optoelectronics and Biomedical Photonics
Development of compact high power 3um laser sources for biomedical application.
Supervisor: Prof Edik Rafailov e.rafailov@aston.ac.uk
Area of Research: Biomedical Photonics, Lasers, Modelling, Sensors, Spectroscopy, Devices
Comprises the development of the original design of semiconductor master oscillator fiber power amplifier light source.
Existing 3 um laser sources have either low repetition rates or low pulse energy or long pulse width and offer poor control of printing parameters when used for LIFT. The master oscillator type-I quantum well cascade diode laser will be developed to achieve required high power short pulse operation for seeding fiber amplifier. Both directly modulated and passively mode-locked master oscillator designs will be explored. The latter case will include development of the heterostructures with engineered group velocity dispersion and external cavity configuration to achieve reduced repletion rates. The multistage fiber amplifier will be developed to achieve optimal pulse parameters for efficient dynamic release layer free LIFT methodology. The newly developed hybrid mid-infrared laser system will be integrated into an existing LIFT bioprinting
Applicants should have: An honours degree (1st Class or 2:1 minimum) in physics or closely related subject. Experience working in a laboratory environment. An interest in sensors and devices. A willingness to learn new experimental and analytical techniques.
Contact: Prof Edik Rafailov (e.rafailov@aston.ac.uk) for more details.
Development of a novel screening system for non-invasive cancer detection based on the breath analyses
Supervisor: Prof Edik Rafailov e.rafailov@aston.ac.uk
Area of Research: Biomedical Photonics, Lasers, Modelling, Sensors, Spectroscopy, Devices
The goal is to combine advanced knowledge in quantum cascade lasers (QCLs), MIR photodetectors, and spectroscopy to create a highly sensitive diagnostic tool. The breath analyser is a valuable method for the early detection of a range of cancers, including colorectal cancer. The aim of this study is to investigate and characterise the chemical patterns associated with the breath of colorectal cancer patients and identify potential expiratory markers of this disease. The distinct breath fingerprint holds promise for early detection and monitoring, presenting a non-invasive and patient-friendly approach to improving clinical outcomes. This breath-based screening technology has the potential for widespread adoption by healthcare providers, offering ease of accessibility to citizens. The only requirement for participants is to avoid eating or smoking for a few hours before providing a breath sample.
Applicants should have: An honours degree (1st Class or 2:1 minimum) in physics or closely related subject. Experience working in a laboratory environment. An interest in sensors and devices. A willingness to learn new experimental and analytical techniques.
Contact: Prof Edik Rafailov (e.rafailov@aston.ac.uk) for more details.
The development of a wearable LDF and fluorescence spectroscopy device for cardiovascular monitoring
Supervisor: Prof Edik Rafailov e.rafailov@aston.ac.uk
Area of Research: Biomedical Photonics, Modelling, Sensors, Spectroscopy, Devices
This research project focuses on the development and validation of a wearable laser Doppler flowmetry (LDF) and fluorescence spectroscopy (FS) device for real-time monitoring of blood flow and metabolic tissue activity.
The primary goal is to advance wearable technology by integrating LDF and FS capabilities into a compact, cost-effective device. This novel technology aims to enable continuous, non-invasive monitoring of cardiovascular and metabolic health parameters, providing unprecedented insights into microcirculation and tissue activity.
Applicants should have: An honours degree (1st Class or 2:1 minimum) in physics or closely related subject. Experience working in a laboratory environment. An interest in sensors and devices. A willingness to learn new experimental and analytical techniques.
Contact: Prof Edik Rafailov (e.rafailov@aston.ac.uk) for more details.
Development of 3D scaffolds based human neural networks using novel bio-printing technology
Supervisor: Prof Edik Rafailov e.rafailov@aston.ac.uk
Area of Research: Photonics, Modelling, Sensors, Spectroscopy, Devices
The main challenge is to produce biocompatible, architecturally defined 3D scaffolds that reliably support the growth and functional integration of iPSC-derived neurons and astrocytes. The scaffold must not only sustain viability but also enable network architectures that mimic in vivo connectivity, allowing meaningful physiological investigation.
The aim is develop 3D scaffolds for iPSC-derived human neural networks and skin models, integrating machine learning (ML) and artificial intelligence (AI) for scaffold optimisation and neural network analysis.
Applicants should have: An honours degree (1st Class or 2:1 minimum) in physics or closely related subject. Experience working in a laboratory environment. An interest in sensors and devices. A willingness to learn new experimental and analytical techniques.
Contact: Prof Edik Rafailov (e.rafailov@aston.ac.uk) for more details.
Novel photonics based techniques for biomedical applications
Supervisor: Prof Edik Rafailov e.rafailov@aston.ac.uk
Area of Research: Photonics, Modelling, Sensors, Spectroscopy, Devices
Microvascular blood flow is a key indicator of tissue health and disease progression. Current measurement techniques typically choose between quantification (e.g. laser Doppler flowmetry, OCT-angiography), or wide-field measurements (e.g. laser speckle imaging), limiting clinical utility. Multiple exposure speckle imaging in principle offers both, but requires much more complex data processing, both in terms of hardware and data analysis.
The PhD candidate will develop advanced models based on analytical and Monte Carlo methods to convert multiple exposure speckle imaging data into quantitative blood flow information, and develop signal and data processing methods to advance multiple exposure speckle imaging systems as a clinical tool. This work will build on the laser Doppler flowmetry work developed by Professor Rafailov and speckle imaging work at industry partner Occuity, a leading medical engineering company based in Reading, and will be split between Aston and Reading.
Applicants should have: An honours degree (1st Class or 2:1 minimum) in physics or closely related subject. Experience working in a laboratory environment. An interest in sensors and devices. A willingness to learn new experimental and analytical techniques.
Contact: Prof Edik Rafailov (e.rafailov@aston.ac.uk) for more details.
Laser technologies in developing advanced human stem cell models
Supervisor: Dr Sergei Sokolovski s.sokolovsky@aston.ac.uk
Ambition: Combined laser nanoscaled 3D printing and NIR laser biostimulation will be exploited to develop fast maturating functional neural system 3D models from human pluripotent stem cells.
Dementias are main course of high morbidity and mortality in elderly population strata. The development of relevant human neuronal models revolutionizes fundamental medical research and drug discovery. A major challenge of this approach is that human induced pluripotent stem cells (hiPSCs) derived neural models used for studding brain in health and disease are grown in two dimensional systems, which does not mimic in vivo 3D interactions and the myriad developmental cues cells would receive in vivo. However existing 3D printing approaches don’t give a required architecture in forming of stable 3D neuronal networks in time.
The next leap for 3D bioprinting will be the development of nano-scaled biocompatible scaffolds to grow functioning 3D cluster of human neuronal cells accompanied with laser stimulation to enhance the maturation of cells to provide new critically important biophotonic platform for neuroscientists and clinicians working in the field of neurodegeneration research and drug discovery.
From candidate(s) we expect background in laser physics or/and cell biology (honours degree, 1st clas of 2:1 minim BSc/MSc), two photon 3D printing.
Contact: Dr Sergei Sokolovski (s.sokolovsky@aston.ac.uk) for more details.
Biocompatible Microelectrodes for Electrophysiological Study of Brain Pathologies
Supervisor: Dr Petro Lutsyk p.lutsyk@aston.ac.uk
Project Summary, Aim and Objectives:
• Background.
Epilepsy is a common disease where a sudden outburst of electrical activity in the brain causes serious seizures. In severe cases, patients might be subjected to surgical removal of the pathological brain tissue. Measurements of electrical signals from brain tissue samples are one of the most appropriate scientific approaches to study this condition. However, the study of such brain tissue is limited by the very short lifetime of the tissue on the current microelectrode experimental setup due to the lack of supplemented oxygen and carbon dioxide. Therefore, there is an immense need to overcome this challenge by using gas-permeable microelectrodes.
• Aim and Objectives.
This PhD studentship project aims to develop novel microelectrodes for brain tissue activity measurements. We will do so by a synergy of combining new nanomaterials and advanced microfabrication technologies of ink-jet printing and 2-photon polymerisation (2PP). The goal is to resolve the current technology problem of short-lived brain tissue allowing to gain pioneering insights into the electrical activity of the brain. For example, such prolonged brain studies can provide ground-breaking information about epileptic brain patterns and accelerate the development of effective anti-epileptic treatments. The following Research Objectives (ROs) will be pursued:
• RO1: To develop & optimise new nanocomposite materials for the fabrication of innovative microelectrodes using 2PP and inkjet printing technology.
• RO2: To deploy the microelectrodes to investigate its biocompatibility for electrophysiological & pharmacological studies of brain tissues.
This project will benefit from close interdisciplinary collaboration at the interface of neuroscience, nano-engineering, and microfabrication within the Aston Institute of Photonic Technologies (AIPT) and Aston Institute of Health and Neurodevelopment (IHN).
Knowledge and skills required in applicant:
Preferred skill requirements include knowledge/experience of nanomaterials processing, ink jet printing, 2-photon polymerisation, experimental characterisation of liquid/solid samples by electrical measurements, electrophysiology signal recordings, working with cultured brain tissues.
Contact: Dr Petro Lutsyk (p.lutsyk@aston.ac.uk), Dr Stuart Greenhill (greenhis@aston.ac.uk) or Prof David Webb d.webb@aston.ac.uk for more details.
Machine Learning and Unconventional Computing
Unconventional optical communicating
Supervisor: Prof Sergei K. Turitsyn s.k.turitsyn@aston.ac.uk
Contact: Prof Sergei Turitsyn (s.k.turitsyn@aston.ac.uk) for more details.
Optical reservoir computing
Supervisor: Dr Egor Manuylovich e.manuylovich@aston.ac.uk
Contact: Dr Egor Manuylovich(e.manuylovich@aston.ac.uk) for more details.