Positions

Loughborough University

Project Objectives

Loughborough University offers a 3-year fully funded PhD position to work on an exciting project that is part of the prestigious Loughborough University Vice Chancellor’s PhD Cluster – Diverse Research in Inclusive Vehicle Environments Research Cluster (DRIVE-RC). The successful PhD candidate will join a cohort of five students who will be working on different multidisciplinary aspects of inclusivity within vehicular environments and will be supported by Loughborough’s Transportation AI Innovation Centre .

How to apply

For more information and application, please see here .

University of Warwick

Project Objectives

The PhD project focuses on developing computational models to better understand material failure under dynamic loading, particularly in ductile fractures. Using phase-field techniques, it will explore processes such as strain localisation, void growth, and crack propagation. AI-driven tools will support efficient parameter calibration and uncertainty quantification, ensuring improved accuracy and practical applications in engineering.

Outcomes

• Developed a phase-field model for simulating high-rate ductile fractures under dynamic loading conditions.
• Enhanced understanding of the interplay between strain localisation, void formation, and crack propagation.
• Developed AI-enhanced tools for efficient parameter calibration and uncertainty quantification.
• Continuum mechanics theory.
• AI and machine learning fundamentals for scientific applications.
• Programming for scientific computing (e.g., Python, C++/Fortran).

Skills that the student will acquire

• Continuum mechanics theory.
• AI and machine learning fundamentals for scientific applications.
• Programming for scientific computing (e.g., Python, C++/Fortran).

How to apply

For full details of the funding available and how to apply follow this link. This is an open-ended deadline and will close upon identification of a suitable student.

More Information

For more information contact Dr Emmanouil Kakouris (Emmanouil.Kakouris@warwick.ac.uk)

University of Leicester

Description of the 4-year PhD project

Siemens Healthineers is a global leading company in the manufacture of MRI magnets. A key challenge for the company is the generation of ghosting artefacts that arise as part of the imaging process. These artefacts present challenges for medical professionals attempting to draw diagnoses from the images. The ghosting artefacts arise due to the strong uniform magnetic field across the bore of the magnet being disturbed by eddy currents and mechanical vibrations of the conducting components of the scanner. Current processes to remove the effects are based on post-processing the images, but with the move towards more sustainable magnet designs, predicting the field perturbations and understanding how to account for them has become very challenging.

The aim of this PhD is to develop a computational tool for predicting field inhomogeneities across the bore of the MRI imaging region and to understand how this can be used as part of the imaging process to minimise ghosting. The research also aligns with our wider developing research activities on predictive digital twins.

The methodology of the PhD will be as follows

1. Gain a good physical understanding of the physical engineering processes in the design and build of MRI scanners.

2. Understand the suite of current computational tools developed by Ledger and Gil to predict magneto-mechanical coupling in MRI scanners and extend this software to predict complex situations in 3D and apply reduced order models for computational efficiency.

3. Build on existing software bases that lead to tools that can be used by industry by working effectively with software libraries.

4. Gain familiarity with current techniques used for removing ghosting effects and how these could benefit from the additional insights provided by an accurate prediction of the field inhomogeneities across the bore of the MRI imaging region.

As well as the outstanding opportunities for collaboration with teams of engineers, computer scientists and mathematicians at the University of Leicester, the PhD student will have the opportunity to collaborate with the teams of computational engineering researchers at the Zienkiewicz Institute for Modelling and AI, Swansea University and with the industrial supervisor at Siemens Heathineers Magnet Technology. The expected start date is September 2025. Funding is available for UK applicants.

How to apply

For full details of the funding available and how to apply follow this link and then click on “Apply Mathematics PhD”. Deadline for applications is 31st January 2025.

More Information

For more information contact Prof Paul D. Ledger (pdl11@leicester.ac.uk)

University of Warwick

HetSys is an EPSRC-supported Centre for Doctoral Training (CDT) which trains people to challenge current state-of-the-art in computational modelling of heterogeneous, real-world systems across a range of research themes spanning quantum, atomistic and continuum models of materials and molecules. The HetSys team are now recruiting a new cohort of enthusiastic students from across the physical sciences who enjoy using their mathematical skills and thinking flexibly to solve complex problems to join our EPSRC Centre for Doctoral Training in Modelling of Heterogeneous Systems at the University of Warwick, UK. Our exciting range of new PhD projects for Oct 2025 can be found on our webpage.

HetSys is built around a closely knit, highly collaborative team of academics from science departments across Warwick (including Physics, Engineering, Chemistry, Life Sciences, Mathematics, Statistics and the Warwick Manufacturing Group) at Warwick. With its project partners HetSys is developing talented, energetic PhD students to push boundaries in this exciting field. The students will inspire new ideas, approaches and innovation and become future leaders in developing new technologies.

Full funding is available for 10+ candidates, including those who meet the required UK residency criteria plus a small number of international students.  We require at least a 2(i) honours degree at BSc or an integrated masters degree (e.g. MPhys, MChem, MSci, MEng etc.) in a physical sciences, mathematics or engineering discipline. PhD duration is 4 years including the training programme which runs over the first 2 years with a gradual transition from fully training to fully research. The studentships pay a stipend to cover maintenance as well as paying the university fees and research training support. The stipend is at the standard UKRI rate (for 2024/25 that is £19,237), and all fees plus a research training support grant including a generous travel budget and HPC access are also fully funded.

The first-round deadline for all applicants is 20 January 2025. Interviews will be held on 12 February 2025.

Japan Agency for Marine-Earth Science and Technology

Aim of Position

In order to support and encourage talented early career researchers who have just obtained Ph.D. to further develop their research theme, JAMSTEC launched the program to foster them in 2014. This program renamed as “JAMSTEC Young Research Fellow (JYRF)” in 2019, has been producing excellent researchers who are active internationally.
JAMSTEC invites early career researchers who are expected to play an active role in the international community and who are willing to take on challenging research activities. This year there are about five JYRF positions to be filled.

Job Description

Successful fellows are expected to independently conduct scientific work on research topics of their own choice or to become involved in research already being conducted at JAMSTEC. 
Research grants will be provided to successful fellows to facilitate the smooth start-up of their research at JAMSTEC (1,000,000 for the first fiscal year and 500,000 for the second and third years each). The successful fellow will also have access to the necessary facilities and equipment in JAMSTEC during the contract period.
Each successful fellow will be assigned a mentor and a sub-mentor. They are responsible for providing advice on the successful fellow’s research progress and support for the all aspects of research life.

JAMSTEC’s Research and Development:
https://www.jamstec.go.jp/e/about/research/

Research Vessels, Facilities and Equipment:
https://www.jamstec.go.jp/e/about/equipment/

[Description of Duties]
(Immediately upon employment)
Successful fellows will be expected to engage in the research subject which is authorized by JAMSTEC in the assigned affiliation under direction of leaders.

(The scope of possible changes)
The duties designated by JAMSTEC

*The assignment to an institute will be determined by the screening committee.
*There may be a change in affiliation in the event of a reorganization of JAMSTEC.

[Relevant Research Fields]
Any natural science or engineering field

Requirements

Applicants are required to have a Ph.D. in natural science or engineering field (including applicants expected to obtain a Ph.D. by the effective date of employment.)
*Specific dates regarding eligibility are below;
・ Applicants who have already been awarded a Ph.D. on or after August 1, 2019
・ Applicants who are expected to obtain a Ph.D. by September 30, 2025

Closing Date

August 26, 2024 at 23:59 in Japan time 
*All the required documents, including the letter of recommendation, should be submitted from the website by this time and date.
*Depending on the situation of applications, the closing date may be extended.

More Information

For more information and to apply, visit https://www.jamstec.go.jp/e/work_with_us/jobs/details/jyrf20240826 or contact Dr Ettore Barbieri (e.barbieri@jamstec.go.jp).

University of Warwick

Unlock a unique opportunity with a fully-funded PhD Project

Join us in a groundbreaking research endeavour aimed at revolutionising design of composite materials for cryogenic hydrogen applications in aerospace. We are seeking an enthusiastic student to lead a challenging PhD project focused on developing a multiscale methodology driven by Artificial Intelligence (AI) and mechanistic modelling across the scales to provide state-of-the-art design tools to optimise composite materials for problems associated with cryogenic hydrogen storage. This project is funded by the EPSRC HetSys II CDT at the University of Warwick, in partnership with the National Composites Centre (NCN).

The Challenge

Hydrogen fuel is envisaged as a key pillar in a future green economy with the potential to decarbonise aerospace industry. Efficient design of advanced composite materials that can sustain harsh cryogenic hydrogen applications is critical to achieving decarbonisation goals and paving the way for a more sustainable future. Multi-scale modelling methodologies that integrate modelling concepts from physics and engineering and are accelerated with AI/Machine Learning (ML), are crucial for paving the way for a more sustainable design of composite materials. This project will develop a radically-new predictive platform by leveraging cutting-edge techniques of mechanistic and AI-driven frameworks to pioneer new design ways for composites towards a greener future.

Why Warwick?

The University of Warwick has been awarded £11 million to train PhD students in computational modelling within the Centre for Doctoral Training in Modelling of Heterogeneous Systems, known as HetSys II. The new centre which spans seven departments and three university research centres will train 50 PhD students to use computational modelling to tackle pressing global sustainability challenges.

Who Should Apply?

We’re looking for candidates with a minimum of an upper second-class honours’ degree (or equivalent) in Engineering, Maths, and Physics – candidates with Chemistry background interested in multiscale materials modelling will also be considered. This exclusive opportunity is only open to UK residents. For more information and to apply, visit https://warwick.ac.uk/fac/sci/hetsys/apply/ or contact Dr Lukasz Figiel (l.w.figiel@warwick.ac.uk).

Benefits

• Fully funded PhD studentship at a leading academic institution.

• Advanced training in computational modelling within a multidisciplinary cohort

• Gain hands-on experience in cutting-edge AI-based multiscale modelling

• Contribute to groundbreaking collaborative research with real-world impact on sustainability and industry.