Integrated Micro and Nano Systems

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 project aims to address a need for the Centre of Ecology and Hydrology who monitor Ammonia in the environment, especially in areas of concern such as pig farms where the high ammonia content can affect the environment.

Currently sensors of sufficient sensitivity for environmental monitoring of ammonia are not readily available for continuous readout, instead samples are collected monthly and analysed in a laboratory with no record of distribution timeline. This project will combine a previously investigated zinc nanowire detection mechanism with an optical ring resonator aiming to give continuous data at the required sensitivity enabling accurate chemical/environmental monitoring.

The successful applicant will initially work with Heriot Watt to model the device and produce a design before learning fabrication techniques in Edinburgh University cleanroom and fabricating devices. Working with the Centre of Ecology and Hydrology to expose the samplesand the performance would then be characterised at the Optics facilities at Heriot Watt.

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.

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

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

Further information and other funding options.

The Centre for Electronics Frontiers (CEF) led by Regius Chair of Engineering Prof Prodromakis, brings together diverse and interdisciplinary expertise for transforming modern society through technology. Our ambition is to push the frontiers of electronics through emerging technologies, disrupting current ways of thinking by innovating advanced nano/biosensors, safe and efficient energy storage solutions and novel hardware for AI. We are offering prospective PhD students the opportunity to join our team, interested in devoting their passion for addressing some of the challenges we have identified.

The project aims at exploring the potential benefits of employing software optimization techniques for modelling and training Large Language Models (LLMs), with a specific focus on Transformers, targeting various unconventional hardware architectures and computing domains (Binary, Analog, Bitstream). The project targets developing Python-based libraries for training and inference that are friendly to unconventional computing domains. These libraries should be eventually integrated with PyTorch and/or TensorFlow to facilitate modelling and quantization-aware training for different AI hardware architectures.

The required skills are as follows:

• Excellent programming skills using Python (mandatory). 
• ML/AI modelling using PyTorch or TensorFlow (mandatory). 
• DNN quantization and pruning techniques. 
• TCL and Makefile scripting. 
• Basics of computer architecture. 

Group website: https://cef.eng.ed.ac.uk/

The University of Edinburgh is committed to equality of opportunity for all its staff and students, and promotes a culture of inclusivity: https://www.ed.ac.uk/equality-diversity

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 applicants who qualify as Home applicants.

To qualify as a Home student, you must fulfil one of the following criteria:

• You are a UK student

• You are an EU student with settled/pre-settled status who also has 3 years residency in the UK/EEA/Gibraltar/Switzerland immediately before the start of your Programme. (International students not eligible).

Further information and other funding options.

The Centre for Electronics Frontiers (CEF) led by Regius Chair of Engineering Prof Prodromakis, brings together diverse and interdisciplinary expertise for transforming modern society through technology. Our ambition is to push the frontiers of electronics through emerging technologies, disrupting current ways of thinking by innovating advanced nano/biosensors, safe and efficient energy storage solutions and novel hardware for AI. We are offering prospective PhD students the opportunity to join our team, interested in devoting their passion for addressing some of the challenges we have identified.

The project aims at exploring the potential promise of the In-Memory Computing (IMC) concept to target the bottlenecks of AI hardware. Digital IMC is proposed to bridge the Von-Neumann performance gap for AI applications where massive data workloads are consumed. However, the conventional binary computing domain degrades the benefits of IMC due to its computational complexity. The project targets exploring different unconventional computing domains (like Stochastic and Quasi-Stochastic) for IMC. Emerging technologies, with a specific focus on RRAMs, are proposed to increase the on-chip computing memory capacity.

The required skills are as follows:

• Mixed-Signal IC design using Cadence Tools (mandatory).
• Memory/SRAM design (mandatory).
• Previous experience in Tape-outs and Chip Testing.
• RRAMs and/or other Emerging Devices.
• TCL and Makefile scripting.

Centre for Electronic Frontiers (CEF) website: https://cef.eng.ed.ac.uk.  

The University of Edinburgh is committed to equality of opportunity for all its staff and students, and promotes a culture of inclusivity. Please see details here: https://www.ed.ac.uk/equality-diversity.

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 applicants who qualify as Home applicants.

To qualify as a Home student, you must fulfil one of the following criteria:

• You are a UK student

• You are an EU student with settled/pre-settled status who also has 3 years residency in the UK/EEA/Gibraltar/Switzerland immediately before the start of your Programme. (International students not eligible)

Further information and other funding options.

The Centre for Electronics Frontiers (CEF) led by Regius Chair of Engineering Prof Prodromakis, brings together diverse and interdisciplinary expertise for transforming modern society through technology. Our ambition is to push the frontiers of electronics through emerging technologies, disrupting current ways of thinking by innovating advanced nano/biosensors, safe and efficient energy storage solutions and novel hardware for AI. We are offering prospective PhD students the opportunity to join our team, interested in devoting their passion for addressing some of the challenges we have identified.

The adoption of sensory networks has been steadily increasing across various technology domains including healthcare, environmental monitoring, industrial automation, smart homes, agriculture, transportation, security, and defence. The number of these sensory nodes is projected to grow exponentially, reaching 75 billion by 2025 and escalating to 125 billion by 2030. This substantial increase will result in a vast amount of raw data that needs to be processed. This Von Neumann-like bottleneck adds more power and performance penalties to the already struggling conventional technologies in the era of AI. To mitigate this, it is crucial to adopt different unconventional technologies that span emerging electronic/photonic technologies and in-memory computing to push computational capabilities closer to the edge. Ongoing research at CEF focuses at defining a novel approach to embed intelligence locally enabling training at the edge by developing novel in-sensing processing elements (enabling electronic and photonic control). We are developing an in-sensor processing architecture using emerging devices (RRAMs) for image classification; however, it can be used in various domains such as light, RF, IR, and gas.

This PhD will be supervised by Prof Themis Prodromakis and Dr Andreas Tsiamis and aims to explore architecture routes and novel thin film materials for realising and characterising micro and nanoscale memristive devices that can be controlled electrically and optically. Device architectures include metal-insulator-metal vertically stacked structures, planar nanodevices, or hybrid architectures that extend from traditional designs. Material investigation may focus on transparent or semitransparent conducting electrodes and active single or bilayer dielectric configurations such as metal-oxides, 2D materials, organic materials etc. The PhD candidate will be trained in and consequently further develop fabrication techniques, including thin film deposition, device patterning and etching. The research will also contribute towards the development of the test apparatus and experimental procedures to allow device characterisation with optoelectronic control. Ultimately the devices may be integrated with CMOS electronics. The research is affiliated with the EPSRC programme “Pro-Sensing” that is developing next-generation semiconductor technologies for smart-imaging applications.

The successful candidate will join our team which includes researchers at the Centre for Electronics Frontiers, the Institute for Integrated Micro and Nano Systems and the wider College of Science and Engineering. They will also have the opportunity to work with our collaborators at the Institute of Photonics, University of Strathclyde. They will be based within the Institute for Integrated Micro and Nano Systems and will be trained to access our class 10 Micro and Nanofabrication cleanrooms at the Scottish Microelectronics Centre, complemented by our state-of-the-art semiconductor characterisation facilities.

Group website: https://cef.eng.ed.ac.uk/

The University of Edinburgh is committed to equality of opportunity for all its staff and students, and promotes a culture of inclusivity: https://www.ed.ac.uk/equality-diversity

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 applicants who qualify as Home applicants.

To qualify as a Home student, you must fulfil one of the following criteria:

• You are a UK student

• You are an EU student with settled/pre-settled status who also has 3 years residency in the UK/EEA/Gibraltar/Switzerland immediately before the start of your Programme. (International students not eligible).

Further information and other funding options.

The Centre for Electronics Frontiers (CEF) led by Regius Chair of Engineering Prof Prodromakis, brings together diverse and interdisciplinary expertise for transforming modern society through technology. Our ambition is to push the frontiers of electronics through emerging technologies, disrupting current ways of thinking by innovating advanced nano/biosensors, safe and efficient energy storage solutions and novel hardware for AI. We are offering prospective PhD students the opportunity to join our team, interested in devoting their passion for addressing some of the challenges we have identified.

The adoption of sensory networks has been steadily increasing across various technology domains including healthcare, environmental monitoring, industrial automation, smart homes, agriculture, transportation, security, and defence. The number of these sensory nodes is projected to grow exponentially, reaching 75 billion by 2025 and escalating to 125 billion by 2030. This substantial increase will result in a vast amount of raw data that needs to be processed. This Von Neumann-like bottleneck adds more power and performance penalties to the already struggling conventional technologies in the era of AI. To mitigate this, it is crucial to adopt different unconventional technologies that span emerging electronic/photonic technologies and in-memory computing to push computational capabilities closer to the edge. Ongoing research at CEF focuses at defining a novel approach to embed intelligence locally enabling training at the edge by developing novel in-sensing processing elements (enabling electronic and photonic control). We are developing an in-sensor processing architecture using emerging devices (RRAMs) for image classification; however, it can be used in various domains such as light, RF, IR, and gas.

This PhD will be supervised by Prof Themis Prodromakis and Dr Spyros Stathopoulos and aims to develop 3D multi-level RRAM structures for electronic and optical applications. This idea builds and expands upon our metal-oxide RRAM platform by vertically stacking functional oxide layers with varying functionalities in a Metal-Insulator-Metal-Insulator-Metal (MIMIM) fashion. Given the versatility of metal-oxides as functional materials different behaviours can be imprinted into the different active layers. These could comprise a selection layer, a memory layer and a sensory layer all independently controlled. The PhD student will develop, fabricate and characterise such structures targeting different applications for electronic and sensory elements. The research is affiliated with the EPSRC programme “Pro-Sensing” that is developing next-generation semiconductor technologies for smart-imaging applications.

The successful candidate will join our team which includes researchers at the Centre for Electronics Frontiers, the Institute of Micro and Nano Systems and the wider College of Science and Engineering. They will also have the opportunity to with our collaborators at the Institute of Photonics, University of Strathclyde. They will be based within the Institute for Integrated Micro and Nano Systems and will be trained to access our class 10 Micro and Nanofabrication cleanrooms at the Scottish Microelectronics Centre, complemented by our state-of-the-art semiconductor characterisation facilities.

Group website: https://cef.eng.ed.ac.uk/

The University of Edinburgh is committed to equality of opportunity for all its staff and students, and promotes a culture of inclusivity. Please see details here: https://www.ed.ac.uk/equality-diversity

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 applicants who qualify as Home applicants

To qualify as a Home student, you must fulfil one of the following criteria:

• You are a UK student

• You are an EU student with settled/pre-settled status who also has 3 years residency in the UK/EEA/Gibraltar/Switzerland immediately before the start of your Programme. (International students not eligible).

Further information and other funding options.

The Centre for Electronics Frontiers (CEF) led by Regius Chair of Engineering Prof Prodromakis, brings together diverse and interdisciplinary expertise for transforming modern society through technology. Our ambition is to push the frontiers of electronics through emerging technologies, disrupting current ways of thinking by innovating advanced nano/biosensors, safe and efficient energy storage solutions and novel hardware for AI. We are offering prospective PhD students the opportunity to join our team, interested in devoting their passion for addressing some of the challenges we have identified.

The project aims at building large-scale AI accelerators for Large Language Models (LLMs), with a specific focus on Transformers. Diverse hardware optimization techniques can be used, targeting a scalable tile-based Tensor Processing Units (TPUs) engine with massive on-chip global buffers for data-stationary. Systolic Array (SA) architectures with novel spatial dataflows will be utilized, at a large scale, for energy-efficient LLM training and inference. The project targets building full system prototypes in advanced CMOS/FinFET technology nodes (28nm, 16nm). These digital exact computing systems are planned to host/collaborate with unconventional AI architectures with emerging technologies later.

The required skills are as follows:

• Verilog RTL Coding & Testing (mandatory).
• Digital ASIC Cell-based Flow using Cadence or Synopsys Tools (mandatory).
• Previous experience in Tape-outs and Chip Testing.
• Systolic Arrays and AI Architectures.
• SRAM design & Memory Compilers.

Group website: https://cef.eng.ed.ac.uk/

The University of Edinburgh is committed to equality of opportunity for all its staff and students, and promotes a culture of inclusivity. Please see details here: https://www.ed.ac.uk/equality-diversity

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 applicants who qualify as Home applicants.

Home Students:

To qualify as a Home student, you must fulfil one of the following criteria:

• You are a UK student

• You are an EU student with settled/pre-settled status who also has 3 years residency in the UK/EEA/Gibraltar/Switzerland immediately before the start of your Programme. (International students not eligible).

Further information and other funding options.

The Centre for Electronics Frontiers (CEF), led by Regius Chair of Engineering Prof Prodromakis, brings together diverse and interdisciplinary expertise for transforming modern society through technology. Our ambition is to push the frontiers of electronics through emerging technologies, disrupting current ways of thinking by innovating advanced nano/biosensors, safe and efficient energy storage solutions and novel hardware for AI. We are offering prospective PhD students the opportunity to join our team, interested in devoting their passion for addressing some of the challenges we have identified. This project will also be supervised by Dr Cristian Sestito.

The project aims at building accelerators based on Field Programmable Gate Arrays (FPGAs) and suitable to deliver computer vision tasks through Generative AI. Generative Adversarial Networks (GANs) based on Convolutional Neural Networks (CNNs) are promising candidates in this direction: they exploit adversarial learning and feature extraction to execute a multitude of applications, including image dataset generation, image-to-image translation, face frontalisation. Specifically, the project targets deploying applications like this on FPGA-based Systems-on-Chip (SoCs) to be showcased in real-time systems, with an in-depth investigation on optimisation techniques to reach high throughput and low energy footprint (e.g., data quantisation and pruning). This will require preliminary training using software frameworks, like PyTorch or TensorFlow.

The required skills are as follows:

• Knowledge and expertise on FPGA design for AI using Verilog/VHDL (mandatory).
• Knowledge and expertise on training and testing CNNs using SW frameworks, like PyTorch or TensorFlow (mandatory).
• Basic knowledge on Systems-on-Chip based on FPGAs (desirable).
• Previous experience on using 3rd party IP cores for vision applications (desirable).
• Previous experience on training generative AI models (desirable).

Group website: https://cef.eng.ed.ac.uk/

The University of Edinburgh is committed to equality of opportunity for all its staff and students, and promotes a culture of inclusivity. Please see details here: https://www.ed.ac.uk/equality-diversity

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 applicants who qualify as Home applicants.

To qualify as a Home student, you must fulfil one of the following criteria:

• You are a UK student

• You are an EU student with settled/pre-settled status who also has 3 years residency in the UK/EEA/Gibraltar/Switzerland immediately before the start of your Programme. (International students not eligible).

Further information and other funding options.