Fastepo

Title: Novel preforms for Automated Fibre Placement

Location: School of Engineering

Project Type: PhD Research Project (University of Edinburgh PhD)

Funding: Competition Funded

Funding Status: Students Worldwide

Deadline: 14.09.2024

Summary:

The objective of this project is to create innovative AFP preforms with enhanced compressive capabilities. To achieve this, we propose a combined experimental and numerical approach that will help us understand deformation and failure mechanisms while optimizing the internal structure. We have outlined three specific sub-goals:

1. Analyzing the micromechanical behavior of the undulated tow under pure compression, considering variables such as undulation ratio and the angle mismatch between adjacent tows.
2. Investigating microbuckling in damaged samples, with a focus on how it relates to crack density.
3. Homogenizing the response at the mesoscale (tow level) and establishing a failure criteria.

As for the skills and qualifications required, the PhD student will have the opportunity to expand their knowledge in composite manufacturing technologies, advanced testing methods, computational mechanics, and programming. Additionally, there will be ample chances to develop soft skills and engage in scientific networking.

Eligibility criteria:

• Minimum entry qualification: An Honours degree with a 2:1 or higher (or its international equivalent) in a relevant field of science or engineering. It is preferable if the candidate also holds an MSc Degree.

Learn More and Apply.

---

Title: 4D printed composite morphing structures

Location: School of Engineering

Project Type: PhD Research Project (University of Edinburgh PhD)

Funding: Competition Funded

Funding Status: Students Worldwide

Deadline: 14.09.2024

Summary:

This project is centered around the development of a cutting-edge 4D-printed multifunctional composite actuator with enhanced load-bearing capabilities, capable of autonomously adapting its shape. This actuator will be an integral part of a closed-loop control system comprising the following components: (i) 3D-printed embedded sensors, (ii) an electro-thermal 3D-printed multifunctional composite actuator, and (iii) an integrated controller. Our hypothesis posits that a groundbreaking hybrid actuator composed of polymer and unidirectional fiber composite layers will exhibit superior load-carrying capacity at room temperature while providing the necessary flexibility when subjected to temperature changes during actuation.

The project consists of three primary objectives:

Objective 1:

• Fabrication, instrumentation, verification, and validation of 4D-printed composite actuators.

Objective 2:

• Development of a closed-loop autonomous controller that regulates force, intensity, temperature, and deformation, including modeling through Finite Element Analysis.

Objective 3:

• Creation of prototypes, including deployable structures, with an analysis of recovery rate, reversibility, and performance.

Skills to be gained: The PhD student involved in this project will have the opportunity to expand their expertise in multifunctional materials, additive manufacturing, electro-thermo-mechanical testing, instrumentation and control, non-linear mechanics, and computational mechanics. Additionally, numerous opportunities for developing soft skills and engaging in scientific networking will be available.

Eligibility: To be eligible for this position, candidates must hold a minimum entry qualification of an Honours degree at a 2:1 or higher (or its international equivalent) in a relevant science or engineering discipline, with the possibility of additional support from an MSc Degree.

Learn More and Apply.

---

Title: Low-carbon building retrofit by adopting an integrated archetype and net-zero approach

Location: School of Engineering

Project Type: PhD Research Project (University of Edinburgh PhD)

Funding: Directly Funded

Funding Status: Students Worldwide

Deadline: 17.07.2024

Summary:

This PhD opportunity arises from the necessity to develop an innovative approach for achieving Scotland’s net-zero targets in heating with a focus on preserving the built heritage, the surrounding public and private spaces, and the communities reliant on our existing architectural legacy.

Eligibility:

• Undergraduate/Postgraduate students pursuing degrees in the Built Environment and Civil Engineering disciplines.
• Preferably, candidates should possess experience in Scottish and UK building standards and construction practices.
• A background in architectural technology or engineering is highly desirable.
• Proficiency in existing building retrofit strategies and low-carbon heating technologies is advantageous.
• Understanding of the thermodynamic behavior of buildings, energy efficiency, and comprehensive carbon accounting over the lifecycle of structures.
• Knowledge of the UK’s net-zero carbon objectives, legislative requirements, and compliance.
• Awareness of the UK construction industry with a particular focus on existing building practices.

Funding Information:

Tuition fees and stipends are available for both Home/EU and International students.

Learn More and Apply.

---

Title: Tunneling in Organic and Organocatalytic Reactions

Location: School of Chemistry

Project Type: PhD Research Project

Funding: Directly Funded

Funding Status: Students Worldwide

Deadline: Applications accepted all year round

Summary:

This project employs computational chemistry tools to delve into the phenomenon of quantum mechanical tunneling in organic and organocatalytic reactions.

Tunneling is an intriguing occurrence wherein reactions bypass the traditional barrier and instead traverse it through quantum means. Despite the existence of some instances of tunneling reactions, this reactive mechanism remains relatively unexplored in the realm of chemistry. Our objective is to examine the significance of tunneling mechanisms in diverse catalytic reactions and explore the potential for designing novel catalysts that enhance reaction rates by focusing on this pathway.

Prospective candidates should possess, or anticipate obtaining, an undergraduate degree (or equivalent) in chemistry or a closely related field, with a first-class or upper-second class classification.

Learn More and Apply.

---

Title: Smart Surfaces for Anti-Scaling

Location: School of Engineering

Project Type: PhD Research Project (University of Edinburgh PhD)

Funding: Competition Funded

Funding Status: Students Worldwide

Deadline: 27.06.2024

Summary:

Preventing scaling and mineral deposits caused by dissolved materials in water is vital for both the environment and the economy in various industries. Our research focuses on innovative approaches, particularly using smart substrates to mitigate scaling. Recent findings have shown that slippery-liquid-like surfaces can effectively prevent the crystallization of saline droplets, offering potential anti-scaling and anti-fouling solutions.

In this PhD program, you will investigate how different smooth surface coatings impact droplet evaporation, residual material deposition, and deposit adhesion. Your goal will be to develop scaling-resistant surfaces. We seek applicants with strong backgrounds in Engineering or Physics, especially those with expertise in surfaces, fluids, or droplet manipulation.

As a student, you’ll be part of the Wetting, Interfacial Sciences, and Engineering Group within the Institute for Multiscale Thermofluids, collaborating with fellow researchers in the field.

Learn More and Apply.

---

Title: Saline droplet evaporation for engineering applications

Location: School of Engineering

Project Type: PhD Research Project (University of Edinburgh PhD)

Funding: Competition Funded

Funding Status: Students Worldwide

Deadline: 05.07.2024

Summary:

Evaporating droplet arrays are a hot topic in microfluidics and surface patterning. When droplets in an array evaporate near each other, they affect each other’s evaporation rates, creating unique patterns. These patterns have potential applications in smart coatings, electronic printing, and micro/nanostructured materials.

Understanding this process involves considering factors like droplet size, surface properties, and solute concentration. Recent research shows that on slippery liquid-like surfaces, we can control salt crystallization and evaporation rates. This study aims to investigate how initial salt concentration in saline droplets influences array evaporation patterns. By varying droplet concentration and array shape, we can potentially create well-defined patterns for applications in surface design, 3D printing, and microfluidics.

Applicants with an engineering or physics background and expertise in surfaces, fluids, or droplet manipulation are encouraged to apply. You’ll join our vibrant community at the Institute for Multiscale Thermofluids, working on exciting projects related to surfaces and wetting.

Learn More and Apply.

---

Title: Electric Field Control of Liquid Surfaces for Microfluidics

Location: School of Engineering

Project Type: PhD Research Project (University of Edinburgh PhD)

Funding: Competition Funded

Funding Status: Students Worldwide

Deadline: 27.06.2024

Summary:

Dielectrowetting involves controlling liquid droplet wetting on solid surfaces using non-uniform electric fields. By adjusting these fields, we can modify droplet behavior to create precise thin films. This technique offers advantages like low power usage, fast response times, and precise droplet manipulation, with applications in microfluidics, lab-on-a-chip devices, and opto-fluidics.

Previous research demonstrated Dielectrowetting’s ability to create thin films and induce surface wrinkles for optical devices. This Ph.D. program focuses on using static electric fields to create diverse surface shapes and wrinkles on dielectric liquid films. It also explores how these surfaces affect the wetting of immiscible droplets. Additionally, it investigates the use of dynamic electric fields for continuous droplet manipulation in microfluidics.

Applicants with an Engineering or Physics background and experience in surfaces, fluids, or droplet manipulation are encouraged to apply. You’ll join the Wetting, Interfacial Sciences, and Engineering Group within the Institute for Multiscale Thermofluids, working with a dynamic community of researchers in surface science.

Learn More and Apply.

Title: Spontaneous and forced Capillary flows on liquid surfaces

Location: School of Engineering

Project Type: PhD Research Project (University of Edinburgh PhD)

Funding: Competition Funded

Funding Status: Students Worldwide

Deadline: 27.06.2024

Summary:

Capillary imbibition, where a liquid spontaneously infiltrates a porous solid due to surface tension, is vital in nature and technology. We’re exploring what happens when a liquid replaces the solid, a fundamental question in fluid mechanics with engineering potential.

Our recent work has laid the foundation for studying capillary flow within a single liquid pore. In this research project, you’ll investigate capillary flows on liquid surfaces, advancing our understanding and your career.

We’re looking for candidates with an engineering or physics background, proficiency in experimentation and modeling, and experience in surface science, fluid dynamics, or phase change.

Join our community at the Wetting, Interfacial Sciences, and Engineering Group within the Institute for Multiscale Thermofluids, School of Engineering. Benefit from our expertise, publications, collaborations, and international conferences to grow as a scientist.

Learn More and Apply.

---

Title: PhD studentship in Machine Learning

Location: School of Informatics

Project Type: PhD Research Project (University of Edinburgh PhD)

Funding: Directly Funded

Funding Status: Students Worldwide

Deadline: Applications accepted all year round

Summary:

A fully funded PhD opportunity is available, working alongside Dr. Henry Gouk in the School of Informatics at the University of Edinburgh, focusing on the project titled “Enhancing Machine Learning with Context.”

The primary objective of this research is to design and evaluate machine learning systems capable of discovering and utilizing additional contextual information related to the tasks at hand. This approach aims to facilitate the development of more resilient models with reduced data requirements. Contextual information may encompass examples of effective models for similar tasks, natural language descriptions of the phenomena being modeled, awareness of underlying causal mechanisms, or other task-associated metadata.

Candidate Requirements:

1. Proficiency in Python programming and experience with associated machine learning frameworks.
2. Familiarity with concepts like meta-learning, transfer learning, domain adaptation, causal inference, or related domains.
3. Strong mathematical aptitude.
4. Possession of a solid Bachelor’s Honors degree (2.1 or higher, or international equivalent) and/or a relevant Master’s degree in fields such as physics, mathematics, engineering, computer science, or related disciplines.
5. Fluency in English, both written and spoken.
6. A background in statistical learning theory is highly advantageous.

Join us in exploring the exciting realm of Machine Learning with Context, advancing your research career at the University of Edinburgh.

Learn More and Apply.

---

Title: Engineering Education (Remote Laboratories)

Location: School of Engineering

Project Type: PhD Research Project

Funding: Directly Funded

Funding Status: Students Worldwide

Deadline: Applications accepted all year round

Summary:

We welcome applications for a Ph.D. program in Engineering Education, affiliated with the Remote Laboratories initiative at the University of Edinburgh. The supervisory team includes Professor Tim Drysdale, Professor Tim Stratford, and Dr. Jonathan Terry.

Requirements:

• A 2:1 or higher degree in a quantitative field.
• Proficiency in digital skills, including software development.
• Strong communication skills.

Preferred Qualifications:

• Familiarity with programming languages like JavaScript/Vue.js, Python, Go, or C/C++.
• Teaching experience, either informal or formal.
• Background in digital education is a plus.

Join us in this exciting Ph.D. opportunity in Engineering Education.

Learn More and Apply.

---