College of Science and Engineering

The Marie Skłodowska-Curie Actions are the European Union’s reference programme for doctoral education and postdoctoral training. The Marie Skłodowska-Curie Actions fund excellent research and innovation and equip researchers at all stages of their career with new knowledge and skills, through mobility across borders and exposure to different sectors and disciplines. MSCA are open to all domains of research and innovation and encourage international cooperation to set-up strategic collaborations.

See below a list of the supervisors particularly interested in hosting MSCA PF candidates.

Name of Supervisor	Research Areas	Proposed Projects	Postdoctoral Fellow Expertise
Dr. Karl Mason	Machine Learning, Artificial Intelligence, Applied Machine Learning
Dr. Patrick Mannion	Multi-Objective Decision Making, Multi-Agent Systems, Reinforcement Learning, Optimisation, Game Theory
Dr. Waqar Shahid Qureshi	Automated Image Analysis; Deep Learning Architectures; Machine Learning	Automated Framework for Pavement Condition Assessment	Experience in implementing deep learning architectures using PyTorch or TensorFlow
Dr. Effirul Ramlan	Biological computing, Molecular computing, Computing using nature-inspired novel substrates.	Augmenting Foundational Models to Engineer Complex Supramolecular Systems for Nanotherapeutics	PhD in Computer Science / Biochemistry with keen interest in exploring self-organised computing systems
Dr. John McCrae	Natural language processing, knowledge graphs, artificial intelligence, linked data, lexicography, digital humanities	Projects related to the application of natural language processing techniques, especially large language models, to areas related to the construction of knowledge graphs, particularly with application to digital humanities areas	Good knowledge of NLP and related technologies
Dr. Bharathi Raja Chakravarthi	Natural Language Processing
Prof. Peter Corcoran	Computational, Cognitive and Connected Imaging; Computer Vision; Neural Networks (Neural Algorithms, Training Methodologies, Data Augmentations, Generative Data (for Training)); Edge-AI; Neural Speech Processing, Child Speech Processing (text-to-speech and speech-to-text); Multi-modal Imaging (Thermal, NIR, LWIR, Event-Camera, Neuromorphic Vision, etc); Analysis of Human Subjects (Computer Vision, Speech).	"Sensing without Seeing" - using Event Cameras to provide Security and Privacy when analysing human subjects for their cognitive load, emotional state and behaviours. Use cases in advance HCI (Human Computer Interaction); Training Data Synthesis for Event Cameras and use cases in Embedded Imaging (Neural Accelerators); Improved Child Speech Understanding and Speech Generation; Edge-AI (embedded) Child Speech for Smart Toy platform	Image, Video, Speech Analysis; knowledge of state of art neural algorithms (vision transformers, diffusion models, etc); Working with Event Cameras or similar asynchronous data signals; work with spiking or sigma-delta NN or equivalent; embedded programming and/or FPGA experience; Neural Speech experience, particularly in low-resource languages or equivalent; experience with training advanced neural models or complex training frameworks; experience with transfer learning and fine-tuning of advanced neural models/architectures.
Dr. Pedram Masjedi	Developing advanced numerical tools for the aero/hydro-elastic analysis of onshore and offshore wind turbines, as well as composite structures; Computational mechanics, especially meshless methods and Isogeometric Analysis (IGA); Wind Turbines, Aeroelasticity, Fluid Structure Interaction (FSI), Composite Structures, Computational Mechanics, Meshless Methods, Isogeometric Analysis (IGA)		Strong skills in the mathematical modelling of solids and/or fluids, numerical methods and computer programming
Dr. Pouyan Ghabezi	Composites, Additive Manufacturing, 3D printing, Composite material characterization, Advanced manufacturing and testing of composites, Polymers recycling, FEM
Dr. Muhammad Muhammad	Mechanical metamaterials, acoustic metamaterials, elastic metastructures, phononic crystals, topological phononic metamaterials, vibration and acoustics, finite element analysis modelling, structural dynamics, solid and fluid mechanics	Guided acoustic/elastic waves in nonreciprocal nonlinear media; Mechanical metamaterial based orthopaedic implants for biomedical applications	Finite element analysis (COMSOL Multiphysics desirable), structural design and analysis, structural dynamics, wave propagation, mechanical tests
Prof. Kathryn Cormican	Technology innovation management; Responsible service innovation; Digital service innovation; Operational excellence; Project management	Digital service innovation: Capability model and performance indicators	Ability to synthesize and analyse literature, Model development, Advanced statistics e.g. partial least squares structured equation modelling (PLS SEM) Excellent writing skills
Dr. Eimear Dolan	Medical Implants; Local Repeated Therapy Delivery; Foreign Body Response; Innovation	Developing novel medical implants to facilitate the long-term delivery of cell and drug-based therapeutics for diseases such as ovarian cancer and diabetes; particularly interested in active medical implants (particularly soft robotic technologies), their mechanobiological effect on the host cells and coupling advanced therapies to minimally invasive delivery strategies.	Background in Biomedical Engineering or Immunology with an interest in design and assessment of medical implants
Prof. Abhay Pandit	Biomaterials, Drug Delivery, Tissue Engineering, Biomaterial Synthesis	Regeneration by Glyco-functionalisation of Biomaterial Systems	Strong proven experience in molecular biology or biomaterial synthesis, histopathology, good writing skills, independent and proven track record in high impact journals
Dr. Merve Suzan Zeden	Antimicrobial Resistance, MRSA, ESKAPE Pathogens, Bacterial Metabolism, Signalling nucleotides	Molecular Mechanisms of AMR in the ESKAPE Pathogens	Molecular Bacteriology, Bioinformatics, Omics, Biochemistry
Prof. Mark Johnson	Marine Ecology	Improving precision of macroalgal canopy photosynthesis estimates	Simulation modelling, field work, lab analyses
Prof. Alan Ryder	Analytical Chemistry; Bioanalytical sciences; Biophysics; Fluorescence spectroscopy; Raman spectroscopy; Chemometrics/Data analysis.	1) Excitation Emission Fluorescence Lifetime Matrix (EEFLM) spectroscopy: The primary aim of this project is to further develop the Excitation Emission Fluorescence Lifetime Matrix (EEFLM) system (hardware, software, theory, applications) which we can use to validate our ARMES-based methods for the rapid quantitative characterisation of proteins.; 2) Using Total Internal Reflection Fluorescence (TIRF) Microscopy to study the interaction of proteins with surfaces. TIRF localises the fluorescence excitation zone to a nanometre thick (40-200 nm) zone just above the surface of a glass coverslip. This means that only fluorophores in this zone are excited and thus it is an ideal way to study protein-surface interactions; 3) Use of pEEM and single molecule detection (SMD) methods for the quantitative analysis of protein-surfactant interactions. We have an interest to look at how surfactants interact with proteins. The idea being that these types are important for understanding the risks involved in packaging therapeutic proteins in polymer vials. It is also important in the context of understanding problems in the downstream processing of biopharmaceuticals.	Biophysics, Fluorescence Spectroscopy, Optical Instrumentation.
Dr. Brian Ward	Ocean climate; Ocean mixed layer; Air-sea exchange	Turbulence in the mixed layer and its role in the oceanic uptake of carbon dioxide	Oceanography background; Matlab/Python coding; field experience; ocean instruments.
Prof. Louise Allcock	Evolution and systematics (including molecular systematics) of cephalopods; deep sea, with a focus on octocorals (including sea pens); octocoral research comprising of a mix of phylogenetics / systematics and species distribution modelling with a view to supporting conservation of deep-sea habitats.
Dr. Enda Barrett	Cybersecurity, Machine Learning, Artificial Intelligence, Cloud Computing, Energy Management	Building threat detection and projection models using longitudinal machine learning	Computer Science, Statistics, Machine Learning, Programming
Dr. Nazre Batool	Self-supervised Machine Learning, Foundation Models, Multi-modal Data Processing, Image and Video Processing, Artificial Intelligence, Autonomous Vehicles, Robot Vision	Self-supervised learning techniques for Multi-modal data. The candidate can propose a suitable application with substantial impact.	Knowledge of self-supervised learning, experience in image and preferably multi-modal data processing, experience in PyTorch and TensorFlow. Some experience in robotics will be a plus.