About the Project

Imagine faster, clearer MRI scans that can accurately map blood flow in the heart and blood vessels. Simulation-Based Imaging (SBI) is a cutting-edge technology that combines medical imaging with advanced computer simulations to overcome the limitations of current 4D-Flow MRI scans, which can be slow, noisy, and low in resolution. By integrating blood-flow physics directly into the image reconstruction process, SBI aims to generate sharper and more detailed images while significantly reducing scan times.

This PhD project will develop and validate a novel SBI framework for cardiovascular imaging. The research will combine computational fluid dynamics (CFD), medical imaging, high-performance computing, and experimental validation to create next-generation imaging tools for cardiovascular disease.

Main Aim

To develop a new Simulation-Based Imaging framework that combines MRI data with advanced blood-flow simulations to produce faster, higher-resolution, and more clinically useful cardiovascular imaging.

Key Objectives

Develop a novel SBI framework that integrates blood-flow physics with MRI reconstruction.
Create ultra-high-resolution cardiovascular flow images using computational simulations.
Validate the technology using synthetic data, laboratory experiments, and patient imaging datasets.
Demonstrate the potential of SBI to improve cardiovascular diagnosis and treatment planning.

Application Specifications

Applicants must meet the entry requirements for admission to a Doctor of Philosophy (PhD) programme at RCSI University of Medicine and Health Sciences. Candidates should hold a First Class or Upper Second Class Honours degree (2.1) or international equivalent in Biomedical Engineering, Mechanical Engineering, Medical Physics, Computational Engineering, or a closely related discipline.

Essential Requirements

First or Upper Second Class Honours degree (2.1) or international equivalent in Biomedical Engineering, Mechanical Engineering, Medical Physics, Computational Engineering, or a closely related discipline.
Demonstrable knowledge of medical image processing and/or computational fluid dynamics (CFD).
Proficiency in at least one relevant software environment, such as MATLAB, Python, ANSYS, OpenFOAM, or equivalent.
Strong analytical, computational, and quantitative problem-solving skills.
Genuine interest in cardiovascular biomechanics, medical imaging, and computational medicine.
Willingness to undertake both computational and experimental research, including the design, construction, and testing of cardiovascular flow phantoms for MRI validation studies.
Ability to work with pumps, tubing systems, blood-mimicking fluids, and 3D-printed vascular models to recreate physiological blood flow conditions in a laboratory environment.
Excellent written and verbal communication skills in English.
Ability to work independently and as part of a multidisciplinary research team.

Desirable Requirements

Familiarity with finite element, finite volume, or other numerical simulation methods.
Experience with cardiovascular flow experiments, flow-loop systems, Particle Image Velocimetry (PIV), or experimental fluid mechanics.
Experience in designing, manufacturing, or testing physical phantoms, including the use of 3D printing technologies.
Experience with laboratory instrumentation, pumps, sensors, and data acquisition systems.
Evidence of scientific writing, such as a thesis, dissertation, conference paper, journal publication, or technical report.
Interest in translational research and the development of technologies with clinical impact.

About the Project

Main Aim

Key Objectives

Develop a novel SBI framework that integrates blood-flow physics with MRI reconstruction.
Create ultra-high-resolution cardiovascular flow images using computational simulations.
Validate the technology using synthetic data, laboratory experiments, and patient imaging datasets.
Demonstrate the potential of SBI to improve cardiovascular diagnosis and treatment planning.

Application Specifications

Essential Requirements

First or Upper Second Class Honours degree (2.1) or international equivalent in Biomedical Engineering, Mechanical Engineering, Medical Physics, Computational Engineering, or a closely related discipline.
Demonstrable knowledge of medical image processing and/or computational fluid dynamics (CFD).
Proficiency in at least one relevant software environment, such as MATLAB, Python, ANSYS, OpenFOAM, or equivalent.
Strong analytical, computational, and quantitative problem-solving skills.
Genuine interest in cardiovascular biomechanics, medical imaging, and computational medicine.
Willingness to undertake both computational and experimental research, including the design, construction, and testing of cardiovascular flow phantoms for MRI validation studies.
Ability to work with pumps, tubing systems, blood-mimicking fluids, and 3D-printed vascular models to recreate physiological blood flow conditions in a laboratory environment.
Excellent written and verbal communication skills in English.
Ability to work independently and as part of a multidisciplinary research team.

Desirable Requirements

Familiarity with finite element, finite volume, or other numerical simulation methods.
Experience with cardiovascular flow experiments, flow-loop systems, Particle Image Velocimetry (PIV), or experimental fluid mechanics.
Experience in designing, manufacturing, or testing physical phantoms, including the use of 3D printing technologies.
Experience with laboratory instrumentation, pumps, sensors, and data acquisition systems.
Evidence of scientific writing, such as a thesis, dissertation, conference paper, journal publication, or technical report.
Interest in translational research and the development of technologies with clinical impact.

About the Project

Main Aim

Key Objectives

Develop a novel SBI framework that integrates blood-flow physics with MRI reconstruction.
Create ultra-high-resolution cardiovascular flow images using computational simulations.
Validate the technology using synthetic data, laboratory experiments, and patient imaging datasets.
Demonstrate the potential of SBI to improve cardiovascular diagnosis and treatment planning.

Application Specifications

Essential Requirements

First or Upper Second Class Honours degree (2.1) or international equivalent in Biomedical Engineering, Mechanical Engineering, Medical Physics, Computational Engineering, or a closely related discipline.
Demonstrable knowledge of medical image processing and/or computational fluid dynamics (CFD).
Proficiency in at least one relevant software environment, such as MATLAB, Python, ANSYS, OpenFOAM, or equivalent.
Strong analytical, computational, and quantitative problem-solving skills.
Genuine interest in cardiovascular biomechanics, medical imaging, and computational medicine.
Willingness to undertake both computational and experimental research, including the design, construction, and testing of cardiovascular flow phantoms for MRI validation studies.
Ability to work with pumps, tubing systems, blood-mimicking fluids, and 3D-printed vascular models to recreate physiological blood flow conditions in a laboratory environment.
Excellent written and verbal communication skills in English.
Ability to work independently and as part of a multidisciplinary research team.

Desirable Requirements

Familiarity with finite element, finite volume, or other numerical simulation methods.
Experience with cardiovascular flow experiments, flow-loop systems, Particle Image Velocimetry (PIV), or experimental fluid mechanics.
Experience in designing, manufacturing, or testing physical phantoms, including the use of 3D printing technologies.
Experience with laboratory instrumentation, pumps, sensors, and data acquisition systems.
Evidence of scientific writing, such as a thesis, dissertation, conference paper, journal publication, or technical report.
Interest in translational research and the development of technologies with clinical impact.

Simulation-Based Imaging: A Powerful Tool for Improving Cardiovascular Patient Treatment

Post My Job

Dublin, Ireland