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Full NameProfessor Michael Monaghan

School of Engineering

Trinity College Dublin

Webpage:monaghanlab.com

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Research Fields
  • genetics, genomics and molecular biology
  • infectious disease and the immune system
  • cell and developmental biology/regenerative medicine
  • bioengineering/medical devices
  • artificial intelligence/machine learning/data analytics
Postgrad Medical Specialties
  • General Practice
  • Paediatrics
  • Pathology
Medical Subspecialties
  • Cardiology
  • Cardiac Surgery
  • Dermatology
  • Infectious diseases
  • Immunology
  • Oncology
  • Vascular Medicine
My Work

The Monaghan Lab is an interdisciplinary Biomedical Engineering Group focused on state-of-the art approaches in modelling disease in vitro and applying advanced technological approaches to evaluate cell and model patho/normo physiology using human cells and tissues.
Specifically we apply approaches in induced pluripotent stem cell technologies to derive a variety of human cell types (cardiomyocytes, fibroblasts, resident macrophages) in 3D models, subjected to injury and disease to determine new pathways of interrogation and therapy. We have a strong focus in cellular metabolism- which strongly governs cell fate and behaviour, inflammation and bioelectric signalling. We are highly active (but not limited to) in the area of cardiac disease (myocardial infarction) from a materials, cellular therapeutic approach and modelling this disease in vitro.
Over the years we have accumulated unique experience in electroconductive biomaterials applied in tissue engineering, sensor technologies and electrophysiological recordings; induced pluripotent stem cell culture, FLIM metabolism and more recently non-invasive Brillouin assessment of biological viscoelasticity.

Nuno GB Neto, Sinead A O’Rourke, Mimi Zhang, Hannah K Fitzgerald, Aisling Dunne, Michael G Monaghan. Non-Invasive classification of macrophage polarisation by 2P-FLIM and machine learning. Elife 11, e77373

Giuseppe A. Asaro, Matteo Solazzo, Meenakshi Suku, Dahnan Spurling, Katelyn Genoud, Javier Gutierrez Gonzalez, Fergal J. O’ Brien, Valeria Nicolosi & Michael G. Monaghan. MXene functionalized collagen biomaterials for cardiac tissue engineering driving iPSC-derived cardiomyocyte maturation. npj 2D Mater Appl 7, 44 (2023). https://doi.org/10.1038/s41699-023-00409-w

Solazzo, Matteo; Hartzell, Linette; O'Farrell, Ciara; Monaghan, Michael. Beyond chemistry: Tailoring Stiffness and Microarchitecture to engineer highly sensitive biphasic elastomeric piezoresistive sensors. ACS Applied Materials and Interfaces. 2022. 2022, 14, 17, 19265–19277

Solazzo M, Monaghan MG. Structural crystallization of crosslinked 3D PEDOT:PSS anisotropic porous biomaterials to generate highly conductive platforms for tissue engineering applications. Biomaterials Science 9 (12), 4317-4328

Potential Projects

In our group we view a PhD project as fluidic, while still aiming for the original goal. It needs to bring the best potential from a candidate, maximising their previous skills and training them with a critical scientific mindset and technical prowess to make an important impact in the field. It should not be a 'tick-box' exercise but rather execution of research with a clear hypothesis, rigorously tested with state-of-the art approaches. I am open to discussing potential projects with candidates and their interests to see if there is a correct match.
We are a dynamic and motivated group and seek an individual who is open to this. Specifically through the ICAT call, we aim to have a strong clinical application and impact through such a PhD project.

Typical projects would range from the generation of useful in vitro models of the myocardium (ischemic, long QT, Brugada, hypertrophy), metabolic and cell-viscoelastic profiling of immune cells in these contexts. We do not work in isolation and collaborate widely in the fields of immunology, chemistry, physics and medicine.
We have very exciting and diverse approaches in the group -e.g. studying Zebrafish tissue regeneration, electric field therapies, machine learning classification (and predicted guidance) of cell behaviour, natural silk biomaterials for nerve regeneration.
A PhD project in my group would be primarily wet-lab based and would cross over with the skills of established researchers in the lab.

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