STEM Summer Research Dublin Courses

You will earn 6 research credits over 8 weeks, conducting faculty-supervised, hands-on, directed study research projects with results that will culminate in the preparation of a research paper.  You will complete a minimum of 240 hours on research in and out of the laboratory.

Faculty mentors will work closely with you to direct your continued growth and knowledge development in the chosen research topic discipline.

  • Please review your project with your academic or study abroad advisor to ensure it will transfer back to your home school and that you are following your home school’s policies.

Choosing Your Research Project

  • Review Project titles and descriptions below.
  • List 3 (in order of preference) in your personal essay.
  • Program is highly individualized, with limited enrollment.
  • You will need to complete a brief Literature Review in consultation with your research supervisor prior to departure before the start of the program. More details here.
  • We encourage you to contact Arcadia’s Associate Academic Dean of STEM, Equity, & Inclusive Excellence, Dr. Jessie Guinn, to discuss your particular research interests further.

Biology, Microbiology, Neuroscience, Bioengineering, Genetics and Pharmacology, Computer Science, Environmental Science, Botany, Marine Biology, Ecology

Course ID Title Credits Syllabus
DUBI RSLW 392S International Independent Research in STEM Fields 6 PDF

Summer 2022 Research Projects


Animal Evolutionary Embodiment

Discipline: Computer Science
Supervisor: Dr. Abraham Campbell


Virtual Reality has been called an Empathy machine but in the last few years it has fallen short of this vision. One of the issues is that this was way to high a goal to set for our current technology especially as mainstream virtual reality and augmented reality research has been limited before the invention of inexpensive VR HMD's like the Oculus Rift.

Over the last five years there is now widespread availability of tools which can allow this research to be conducted in earnest as before then over the last 30 years this research was restricted to labs with equipment costing over 250,000 euro for CAVE environments to explore this area. Now with affordable VR HMD's this can be brought into the mainstream.

So this project will explore what it’s like to allow a user in a VR world to embody different animal forms. It will be collaboration with Rosie O'Reilly an Artist who is currently in residence within UCD. Rosie is interested in exploring Augmented and Virtual Reality and connecting it with AR and Evolutionary biology where a user could embody lifeforms at different stages of evolution.

The candidate will work with UCD VR lab and the main deliverable will be a VR experience allowing users to become different animals at different points in evolution. The participant will have access to the VR lab during the internship and access to a Quest 2 to complete their research.


User Interfaces for Mission Control

Discipline: Computer Science
Supervisor: Dr. Gavin McArdle

The summer project forms part of a more extensive research programme that concerns the research, design and development of tools and techniques to enhance the efficiency and effectiveness of the fire extinguishing capability of rotary-wing aircraft. Mission control for aerial firefighting requires risk assessment, planning and coordination, supported by accessible and reliable data presented in a usable way. Further, the nature of the task is dynamic requires data to be constantly updated and managed in real-time. Therefore, an innovative online Decision Support System (DSS) consisting of tools for data ingestion, aggregation, analysis, and visualisation is key to the success of the broader researcher programme. Of particular importance is the production of an intuitive user interface to support mission control. For this summer project, the student will work with the project team to scope technologies and methods for developing the user interfaces to support mission control. Multiple interfaces will be available to recognise that different actors will use the system in the air and on the ground. The student will also work on data wrangling and cleaning to source suitable data sources to support the project, such as weather, terrain, water location and land cover, and examine ways to incorporate the data into the tools developed for the research programme.


The Role of the Environment in Learning to Program: Exploring Educational Programming Data with the Blackbox Dataset

Discipline: Computer Science
Supervisor: Dr. Brett Becker

The Blackbox dataset contains the programming activity and source code of around 250,000 students learning to program in Java using the BlueJ development environment. This dataset is relatively new and largely underutilized. This project will explore specific facets of a larger project utilizing this data. The student will work with two PhD students and along with their supervisor, seek to answer questions like the following: What role do compiler error messages play in learning to program? How can they be made better? How does the programming environment affect student learning? Believe it or not, these questions don’t have definitive answers! The answers to questions like these will be of practical use to the overall project and also to the computer science education community in general. The exact nature of the questions to be answered will depend on the progress of the overall project but the intern student can have a part in shaping these questions.

In 2019 an earlier stage of this project resulted in a paper published at the ACM SIGCSE Technical Symposium with the summer intern and the UCD PhD student as co-authors. This project is suitable for students who have a strong interest in databases and programming and has a good chance of resulting in a publication. Some knowledge of Java and SQL (or willingness to learn ahead of time) is advantageous. This project offers an opportunity to contribute to a much larger-scale project and to see how PhD projects work on a daily basis.


Mini green Supercomputer: Reducing the Cost and Carbon Footprint of High Performance Computing Development

Discipline: Computer Science
Supervisor: Dr. Brett Becker

For students who like: programming, hardware/gadgets, carbon reduction and environmental change.

Present-day supercomputers and high performance computing platforms are expensive and consume vast quantities of electricity – often enough to power small cities. The resulting carbon cost of development on these platforms is huge, meaning that only production code is given runtime on these environments. Currently the easiest way for students to write and test parallel code is on multicore computers. However these are not realistic for testing code, particularly as they are typically homogeneous and messages are passed through memory, not over a network.

In this project, you will create a mini heterogeneous ‘supercomputer’. This will consist of several single board computers (such as Raspberry Pi) networked together. Alongside this you will build an application that monitors the status of the system remotely. You will study and gain experience with installing and running parallel computing software. You will gain theoretical and practical skills in system administration, networking and programming. You will also test and benchmark the supercomputer with the same software that is used for current Top500 supercomputers. Machines like this can be used for upper-level parallel computing classes and have positive economic and environmental outcomes.

This project is suitable for students with an interest in programming, networking and gadgets – some hands-on work will be needed. All hardware will be provided to make this a really fun project! The only required experience is some high-level programming – typically a first-year intro course will do (C, C++, C#, Java, or similar).


Computing Crossroads: A Social Computing Project to Help Improve Diversity, Equality and Success in Computer Science

Discipline: Computer Science
Supervisor: Dr. Brett Becker

Computer Science has become one of the most influential academic disciplines in terms of its impact on society. However, as a discipline CS has significant issues with equality, diversity and inclusion - almost every minority group is underrepresented in computing in industry and academia. Many of these issues can be attributed to misconceptions about what CS is and what computer scientists do. These misconceptions are propagated by the media and many other channels.

This project will contribute towards an ongoing public outreach project called Computing Crossroads ( This project features people trained in CS who have gone on to pursue positions in life that are outside “traditional” CS, and those who do “traditional” CS but don’t have a “traditional” CS background. These stories can be inspiring and help to promote better equality, diversity and inclusion in CS by putting a spotlight on inspiring personal stories of CS folks from all walks of life. These stories can serve to break down misconceptions such as “if you major in CS you are stuck in CS”, “I can’t do CS”, “It’s too late to do CS now”, as well as stereotypes like “computer scientists are nerds”. This provides a great opportunity to do primary qualitative research with real human participants and is aligned with other social sciences. This project will live beyond the internship and provides a great chance for a student to contribute to a larger project with a long lifespan. Research will involve interviewing volunteers that the supervisor will put you in touch with.


Electromagnetic Side-channel Radiation Analysis to Identify Software Activities

Discipline: Computer Science
Supervisor: Dr Nhien-An Le-Khac


Time varying electrical currents through conductors tend to generate electromagnetic (EM) radiation. Such radiation emerging from critical components of computers, such as processor and memory, correlates with the machine instructions and data being handled on them. EM side-channel radiation from Internet of Things (IoT) devices are shown to be effective at examining security threats and acquiring forensic insights. However, the real-world application of EM side-channel analysis for digital investigation purposes is obstructed by the lack of suitable tools and the technical expertise. Although certain frameworks, such as EMvidence [1][2], exist to cater to this requirement, the sheer diversity of the IoT ecosystem makes it difficult to support a sufficiently large collection of devices that are commonly encountered in digital investigations. This project aims to address this problem through expanding the capability of acquisition and analysis of EM radiation of IoT devices. The project consists of two phases: (1) data acquisition phase and (2) software behaviour detection phase. In the first phase, software-defined radio (SDR) equipment will be used to capture EM radiation from a wide variety of IoT devices to produce a comprehensive EM radiation dataset. In the second phase, the acquired dataset will be analysed using deep learning techniques to predict the internal software behaviour of the IoT devices. This project will help the student to gain expertise on the exciting field of electromagnetic side-channel analysis using specialized hardware and software tools and also using deep learning techniques to analyse data.


  1. Asanka Sayakkara, Nhien-An Le-Khac (2021), “Electromagnetic Side-Channel Analysis for IoT Forensics: Challenges, Framework, and Datasets” in IEEE Access, vol. 9, pp. 113585 -113598, 2021, DOI:
  2. Asanka Sayakkara, Nhien-An Le-Khac (2021), “Forensic Insights from Smartphones
    through Electromagnetic Side-Channel Analysis” in IEEE Access, vol. 9, pp. 13237 - 13247,
    2021, DOI:


Making Sure Your Conversational AI Knows Right from Wrong

Discipline: Computer Science
Supervisor: Dr Vivek Nallur

Nudge theory has arisen from the Kahneman and Tversky's seminal work on Behavioral Economics. It shows that people can make repeated, predictably irrational decisions, due to cognitive biases that exist among all humans. Nudges are behavioral interventions that arise primarily from human decision-making frailties (e.g., loss-aversion, inertia, conformity). However, not all humans are affected by the same biases, i.e., a nudge that works on one person may not work on another. BigData, when combined with Machine Learning, promises to create a potentially infinitely flexible nudging machine. A software could learn the specific set of biases that affect a particular person, and then adapt its nudges in a highly tailored manner. This is a HyperNudge. Conversational AI (or chatbots, as they are commonly known) have become an acceptable part of online interaction. These agents exist in conversation-enabled devices such as Alexa, and in devices such as smartphones, smartwatches, FitBit, etc. Given that we spend almost all our entire waking hours in close contact with a smart device, it is trivial for the device to nudge our attention to news/views/decision-options that it considers important. Since this decision to nudge occurs at runtime, there is no way to ensure that the conversational agent always behaves in an ethical manner.

Instead of barring AI systems from using any nudges at all, this project proposes to create techniques for chatbots to self-adapt their nudges, in response to expressed human preferences, as well as within constraints of a stated ethical protocol.


Implementing Ethical Rule Bending in AI

Discipline: computer Science
Supervisor: Dr. ek Nallur


To build AI systems that can be trusted to work with human beings we need some confidence that they will act ethically. Apart from the current concerns about bias in AI systems, we also need to embed some ethical principles in AI. This is currently an open research area. Extant ethical agent implementations are mainly two-fold; those designed to follow a set of rules bestowed upon them by the designers, and those focused on increasing the utility of the world. However, these ethical agent models are not competent enough to perform in relatively large and open environments, even though high impact AI agents like autonomous cars or censoring agents operate in such environments. Humans, on the other hand, manage to work effortlessly in these types of environments even with incomplete rule-sets or without a clear understanding of the correct utility models of the world. Humans achieve this by breaking rules when they think it is necessary for pro-social reasons. We believe this Pro-social Rule Bending (PSRB) behaviour is a necessary component for a human-centric ethical AI agent. This project attempts to implement PSRB behaviour in an AI agent, by implementing new computational architecture for a PSRB-capable ethical agent combining multiple AI approaches such as logical and case-based reasoning, machine learning and simulations.

The prospective student must have some experience in python programming, data structures and algorithms, and willing to read/learn quickly about knowledge representation and reasoning, and machine learning. The student needs to be a self-starter, and willing to experiment with code-bases from multiple academic papers/sites.


UAV Command and Control Interface for Integrating Network Slice Enabled Edge Computing Deployments

Discipline: computer Science
Supervisor: Asst. Prof. Madhusanka Liyanage

Unmanned Aerial Vehicles (UAVs) are becoming more prominent due to the advancements envisaged with the 5G and Beyond 5G mobile technologies; that improve the dynamic omnipresence of “devices” and “things”, as in Internet of Things (IoT). The automation projected with the emerging use cases and applications of consumer trading delivery, military, surveillance, remote healthcare, and emergency assistance are only feasible with the launching of UAVs integrated with 5G based technologies for their communication and energy utilization enhancements. In fact, power utilization is a vital requirement for the UAVs that restricts embedding powerful computing (i.e. processor, memory, and storage) and communicating (i.e. transceivers) apparatus. With such restrictions, Command and Controlling (C&C) of the UAV become an arduous objective, especially in an autonomous scenario. Edge computing is one such technology that can be employed for achieving such objectives of unburdening the C&C tasks from the UAV while improving the energy efficiency.

In addition, the concept of network slicing offers a proper framework for provisioning diverse services leveraging the same hardware, such as a UAV. Thus, integrating these concepts/ technologies are imminent for UAVs for its progression. However, a proper common interface, or a firmware is lacking to integrate the UAVs either to the edge, or to the network slices; specifically, designed for the C&C function. Therefore, this research is intending to design and develop a generalized C&C interface for UAVs that can be integrated to network slicing enabled edge computing deployments.

Core Objectives:

  • Learn about UAV command and controlling while studying about its sensor fusion scope.
  • Assemble a UAV or refurbish a UAV to its working condition, and study about its mechanics, working software/firmware.
  • Design and develop the interfacing firmware to offload the C&C parameters to the network slice in the edge server, through the communication channel established between the edge and the UAV.
  • Evaluate the feasibility of the proposed interface with the assembled UAV through trials.


  1. Hermosilla, Ana, Alejandro Molina Zarca, Jorge Bernal Bernabe, Jordi Ortiz, and Antonio
    Skarmeta. "Security orchestration and enforcement in NFV/SDN-aware UAV deployments." IEEE access 8 (2020): 131779-131795.
  2. Faraci, Giuseppe, Christian Grasso, and Giovanni Schembra. "Design of a 5G network slice extension with MEC UAVs managed with reinforcement learning." IEEE Journal on Selected Areas in Communications 38, no. 10 (2020): 2356-2371.
  3. Ning, Zhaolong, Yuxuan Yang, Xiaojie Wang, Lei Guo, Xinbo Gao, Song Guo, and Guoyin Wang. "Dynamic Computation Offloading and Server Deployment for UAV-Enabled Multi-Access Edge Computing." IEEE Transactions on Mobile Computing (2021).


UI/UX Design and Development of a Graphical User Interface (GUI)

Discipline: computer Science
Supervisor: Prof. Eleni Mangina

This project will focus on the UX Design principles for the development of a Graphic User Interface (GUI) for images segmentation. This GUI will form the frontend of a system that utilises datasets related to images captured from a Photon System Instrument (PSI) containing three imaging sensors – fluorescent, RGB, and hyperspectral, with the backend containing the embedded programming elements needed to perform the segmentation tasks. The images are based on data collected from the research group of Prof. Sonia Negrao (Crop Stress Interaction Lab) and they are retrieved from barley plants. Barley is one of the most important cereal crops in the world. The crop has a variety of uses, for animal feeding, the food industry, and for the production of alcohol. However, the crop is very susceptible to waterlogging stress, which causes severe yield loss. Within the lab an experiment seeks to identify waterlogging stress using  methods derived from Artificial Intelligence (AI). This AI platform would train itself using images captured from a Photon System Instrument (PSI) containing three imaging sensors – fluorescent, RGB, and hyperspectral. However, prior to training, this data requires vigorous preprocessing. One such step includes the removal of the plant from its background. As conventional methods have produced unsatisfactory  results, a new segmentation method has been developed using a deep autoencoder network which can accurately segment both RGB and hyperspectral images autonomously. The UX design of the GUI is very important so that it is implemented based on the users’ needs.


Cysteinyl Leukotriene Receptor Signalling & Uveal Melanoma Extracellular Vesicles: Novel Therapeutic Targets or Biomarkers to Improve Patient Outcomes in Metastatic Uveal Melanoma

Discipline: Biomolecular and Biomedical Science/cancer biology
Supervisor: Prof. Brendan Kennedy and Valentina Tonelotto


Our project aims to investigate the disease relevance and therapeutic potential of cysteinyl leukotriene receptors (CysLT) in uveal melanoma (UM) and to identify novel biomarkers for the diagnosis and prognosis of UM. UM is a tumour of the eye with a global prevalence of 1-9/100,000. The mean age-adjusted incidence of UM in Ireland from 2010 to 2015 was 9.5 per million, suggesting that Ireland has one of the highest incidence rates of UM globally. Fatal metastatic disease occurs in about half of patients, with the liver being the most frequent site of metastasis. Unfortunately, there is no effective treatment for metastatic UM (MUM). Furthermore, MUM detection is very challenging. Only 1% of the patients have detectable metastases at the time of primary diagnosis, while up to 30% of them will develop liver metastases within 5 years of treatment. Therefore, novel biomarkers for the diagnosis and prognosis of UM and liver metastasis are under investigation. Recent evidences reveal that UM-derived extracellular vesicles (EVs) display important protein signatures involved in tumorigenesis and metastatic dissemination. Thus, we are developing a protocol to isolate and profile EVs present in patient bloods before and after diagnosis of MUM. We will also isolate EVs from a metastatic UM cell line and evaluate whether drugs antagonising CysLT receptors affect the protein signature or the pro-cancer activity of these EVs. The summer research student will take part to this unique and innovative project, which will accelerate the route towards effective treatments and detection of MUM.


Comparison of the phenotypic profile of Campylobacter jejuni strains isolated from different sources

Discipline: Biomolecular and Biomedical Science
Supervisor: Dr. Tadhg Ó Cróinín

C. jejuni is the most prevalent cause of bacterial gastroenteritis world wide but the inherently high levels of genetic variation in this microorganism makes it difficult to predict the resulting phenotype of individual strains. This project will focus both on the antibiotic resistance profile and on the ability of this microorganism to form biofilm which is critical for its survival in aerobic environments and thus likely a key factor in allowing the pathogen to cause foodborne outbreaks. As part of a collaboration with UCDavis strains isolated from a variety of different sources will be compared using different phenotypic tests including motilty, growth, antibiotic resistance and biofilm formation in an aerobic environment .
The aim of the project is to investigate whether strains isolated from specific sources may be more likely to carry antibiotic resistance genes and whether these in turn could be indicators of a greater ability to form biofilm as indicated by a recent paper from our group. Students interested in taking this project should be highly motivated and interested in the field of infection biology and in particular in antibiotic resistance of microorganisms.

Whelan M, Ardill L, Koide K, Nakajima C, Suzuki Y, Simpson JC, Ó Cróinín T. 2019 Acquisition of fluoroquinolone resistance leads to increased biofilm formation and pathogenicity in Campylobacter jejuni. Scientific Reports Dec 3;9(1):18216.


Association of Gut Barrier Dysfunction in Gastrointestinal Disease Development

Discipline: Biomolecular and Biomedical Science
Supervisor: Dr David Hughes (Cancer Biology and Therapeutics Lab, Conway Institute, UCD)

Gastrointestinal (GI) diseases such as Inflammatory Bowel Disease (IBD) and Colorectal Cancer (CRC) are leading causes of chronic illness (and death for CRC) in many world regions. Although the causes of these diseases are complex, environmental factors, particularly obesity and lifestyle, are known to play a strong role. Recent compelling evidence, some of which my work has helped generate, suggest that commensal microbial dysregulation and exposures to microbial toxins are involved in CRC development. One recent hypothesis is that this occurs through inflammatory-induced weakening of the protective gut mucosal barrier by obesity, dietary/lifestyle, and microbiome factors.

To help explore this hypothesis, the student will measure several biomarkers of gut-barrier function and bacterial translocation (as biomarkers of microbial dysbiosis) by custom ELISAs, e.g., the bacterial product flagellin and the proteins TLR5 – receptor for flagellin and Muc2 (Mucin) – integral to an intact barrier (which modulates the permeability of tight junctions between intestinal tract cells). This will be done in a series of blood samples from non-disease controls (n=180), and patients with IBD (n=130) or CRC (n=125), to assess gut-barrier breakdown from normal to inflammatory to neoplastic. If biomarker levels in serum in disease cases are statistically different than those in controls, it will indicate that the hypothesis is correct. Together, these findings will inform us of gut-barrier function in healthy and disease GI states, and how this may contribute to exposure of bacterial toxins from the gut. Blood-based detection of bacteria and gut-barrier health may allow novel screening strategies for GI disease prevention, diagnosis, and management.


Investigating the role of disease-causing proteins in motor neuron function

Discipline: Biomolecular and Biomedical Science
Supervisor: Dr. Niamh O’Sullivan

My lab studies inherited forms of motor neuron disease, particularly hereditary spastic paraplegia (HSP). Individuals with HSP develop weakness in their legs leading to difficulties walking which is caused by degeneration of the very longest motor neurons. Extensive work in recent years has successfully identified many of the genetic causes underpinning HSP, but there are currently no treatments to prevent, cure or even to slow the course of these diseases. To address this, my lab use cutting-edge genetic engineering to generate novel animal and cellular models of HSP in which to study the molecular events underpinning this disorder. Recently, researchers in my lab have found that HSP-causing genes play a role in the organization of the endoplasmic reticulum (ER) network within motor neurons. The aim of your project will be to study how this impaired ER network contributes to neurodegeneration in motor neurons. You will learn various techniques associated with molecular genetics, confocal microscopic image analysis and the assay of behavioral readouts.

Lab website:


Determining the host response to novel vaccine antigens

Discipline: Biology and Environmental Science
Supervisor: Assoc Prof Siobhán McClean

Antimicrobial resistance is a massive growing problem in the fight against bacterial infections. The number of antibiotics that are effective at treating many bacterial infections is shrinking. Vaccines represent one of the best ways to prevent bacterial infections and have also been shown to reduce antimicrobial resistance [1]. In our lab our aim is develop anti-bacterial vaccines in order to prevent these difficult and challenging infections. We use a proteomic approach to identify highly effective vaccine antigens which prevent infections in mouse models. We have number of vaccine projects ongoing in our laboratory against antibiotic resistant infections such as respiratory infections that impact the lives of people with cystic fibrosis[2]; the tropical infection, melioidosis[ 3, 4]; O157 E. coli and two potentially lethal hospital acquired infections, Klebsiella pneumoniae and Acinetobacter baumannii [5]. We mapped the global prevalence of multidrug-resistant A. baumannii and showed that carbapenem-resistant A. baumannii is widespread throughout Asia and the Americas [5]. We have tested these vaccine antigens in mice and are currently examining the protective immunological responses, including antibody responses and cytokine responses in serum or immune cells. This project will focus on the vaccines for A. baumannii. It will involve using ELISA to determine the levels of antigen specific IgGs in immunised mice. In addition the host response will be further examined by exposing immune cells to antigen and evaluating the profile of cytokines produced using flow cytometry and/ or ELISA. Understanding how the antigens protect against infection is an important stage in progressing the vaccines towards human trials.

The project would suit someone with an interest in immunology, microbiology or biochemistry.


  1. Mishra RP, Oviedo-Orta E, Prachi P, Rappuoli R, Bagnoli F. Vaccines and antibiotic resistance. Curr Opin Microbiol 2012; 15:596-602.
  2. McClean S, Healy ME, Collins C, et al. Linocin and OmpW Are Involved in Attachment of the Cystic Fibrosis-Associated Pathogen Burkholderia cepacia Complex to Lung Epithelial Cells and Protect Mice against Infection. Infection and immunity 2016; 84:1424-37.
  3. Casey WT, McClean S. Exploiting molecular virulence determinants in burkholderia to develop vaccine antigens. Curr Med Chem 2015; 22:1719-33.
  4. Casey WT, Spink N, Cia F, et al. Identification of an OmpW homologue in Burkholderia pseudomallei, a protective vaccine antigen against melioidosis. Vaccine 2016; 34:2616-21.
  5. Ma, C., & McClean, S. (2021). Mapping Global Prevalence of Acinetobacter baumannii and Recent Vaccine Development to Tackle It. Vaccines, 9(6), 570.


Physiological regulation of UT-B urea transporters

Discipline: Biology and Environmental Science
Supervisor: Dr. Gavin Stewart

Urea transporters, such as UT-B, are used to transport urea across cell membranes and are located in a wide variety of tissues - such as kidney, bladder, colon and brain. They are known to play important functions in the mammalian urine concentrating mechanism, symbiotic relationships with colonic bacteria, and the removal of the toxic waste product urea from the brain. Recent studies have shown alterations in UT-B transporters to be linked to a wide range of clinical conditions, such as bladder cancer and Alzheimer’s Disease. Utilizing cell culture, RT-PCR, western blotting and/or immunolocalization techniques, this project will investigate the cellular pathways involved in the normal physiological regulation of UT-B urea transporters. As well as investigating UT-B expression in various mouse and human tissues, we will also be using cell lines - such as RT4 (bladder), HT29 (colon) or N2a (neurones) - to investigate the effects of external osmolality, urea and protein kinase inhibitors on these important transport proteins. Through these experiments, we aim to obtain new insights in to how these UT-B transporters are physiologically regulated.


A cell-based assay investigating the secretion of collagen and its links to human disease

Discipline: Biology and Environmental Science
Supervisor: Prof. Jez Simpson


The protein collagen is a fundamental building block of the human body. Collagen is synthesised in specialised cells termed fibroblasts, and on secretion it forms long fibrils on the outside of these cells. These fibrils eventually assemble into mature collagen fibres that build structures such as bones. A number of human diseases are associated with incorrect or inadequate secretion of collagen, and these can result in skeletal deformities that severely affect the individuals. One example of these diseases is called ‘osteogenesis imperfecta’. Currently there is a lack of understanding about the molecular mechanisms that regulate collagen synthesis and secretion by cells. Such information is vital for the future development of therapeutic interventions for osteogenesis imperfecta. This project will involve the design and optimisation of a cell-based fluorescence microscopy assay to measure collagen synthesis and secretion by a model fibroblast cell line. Advanced quantitative imaging approaches will be used to measure the rate of collagen synthesis by cells, and these experiments will be complemented by biochemical characterisation of the collagen. The assay developed will then serve as a tool by which factors that influence collagen synthesis and secretion can be measured. It is hoped that this approach will pave the way for a deeper understanding of the molecular and cellular basis of these diseases.


Depicting personality traits in fallow deer (Dama dama) fawns at capture.

Discipline: Biology and Environmental Science/animal behavior
Supervisor: Dr Rainer Melzer

Inter-individual variability in animal behaviour within wild populations is an important component influencing their resilience to external perturbations such as human disturbance, climate and habitat change, disease spread. When such differences are consistent through time, we typically refer to them as personality traits. Certain personality traits would be more suited to react to climate change, for instance, whereas others would respond better to human disturbance. A high variability in personality traits allows animal populations to cope with environmental pressures. This project aims to test the hypothesis that behavioural traits recorded at capture (e.g. reaction to capture and human handling, and behaviour at release) in fallow deer neonate fawns of Phoenix Park are highly repeatable over multiple captures and are a good proxy for their personality. Fawns may cope well with human handling (shy individuals) opposed to fawns that do not tolerate human presence (bold individuals); estimating this inter-individual variability is a very important step forward in understanding animal personality in wild populations. The student will join the Phoenix Park capture team during the fawning season of June 2021 and will collect behavioural data on more than 100 fawns. The Phoenix Park is the largest urban park in Europe, it can be easily reached by bus from UCD, and would give the student the opportunity to enjoy both UCD campus and the field site located in the heart of Dublin. The student will learn how to capture, handle and release deer fawns in June, leaving July for data analysis. This is a unique opportunity for students to gain experience in the field of wildlife research and join an experienced team of 20 students and academic staff with longterm experience in animal behaviour.


Molecular and morphological analysis of CRISPR-Cas9 genome edited Arabidopsis thaliana plants

Discipline: Biology and Environmental Science/Genetics
Supervisor: Dr Rainer Melzer

Lab homepage:

Twitter: @UCDflowerpower

We are interested in the genetic control of flower development in Arabidopsis thaliana. Of particular interest are genes that are important for floral organ number control. We have created a mutant in a transcription factor gene that might be involved in this process using CRISPR-Cas9. You will be involved in a detailed molecular and phenotypic analysis of the CRISPR-Cas9 induced mutant.

Techniques involved comprise DNA isolation, PCR, sequence analysis, plant growth and morphological analyses.


Flower development in Cannabis sativa

Discipline: Biology and Environmental Science
Supervisor: Dr Rainer Melzer

Lab homepage:

Twitter: @UCDflowerpower

Cannabis sativa (hemp) is a species that develops male and female flowers on separate individuals. This mode of reproductive development is very unusual among the flowering plants, the vast majority of which are bisexual. In addition, large variation in the flowering time can be found between different Cannabis cultivars. However, almost nothing is known about the genetic and morphological processes involved in flower development and flowering time control in hemp.

In this project, you will be involved in ongoing research aimed at studying flowering time and sex determination in hemp. We employ molecular genetic and bioinformatic tools. This comprises DNA isolation, gene cloning, qPCR as well as genome and transcriptome analyses.


Electrophilic fluorination of piperdeines and their use to approach the synthesis of fluorofebrifugine

Discipline: Chemistry
Supervisor: Dr Marcus Baumann, School of Chemistry

Febrifugine 1 is a naturally occurring compound of interest based on its anti-parasitic activities. More recently an analogue termed halofuginone has been shown to affect protein synthesis in mammalian cells and has been part of a clinical trial aimed at improving symptoms in patients of Duchenne muscular dystrophy.1 We (and others) have found that 1 undergoes interconversion into isofebrifugine 2 in a process that is likely to proceed via a retro-forward conjugate addition process followed by hemiketal formation.2

As shown in the scheme below, we have recently worked on the conversion of a series of Nprotected piperideines 3 into their corresponding 2-allyl-3-fluoro N-protected piperidines 4 (where PG = protecting group e.g. Boc, Cbz, Ts etc.).3 Depending on the identity of the Nprotecting group up to 95:5 of the cis- to the trans-diastereomer can be found.

Where we want to proceed with this chemistry in the context of this specific project is to use the products (4) to prepare the 3-fluoro version of febrifugine, i.e compound 5. Thus, this project will initially re-investigate our synthesis of fluoro piperidine 4 and then work at converting it to cisfluorofebrifugine 5. Since natural febrifugine exhibits a trans-juxtaposition of the 2,3-substutuents on the piperidine ring we will then use 5 to investigate the cis to trans isomerisation process. This process is akin to the  interconversion between 1 and 2 shown above but avoids the complication of the hemiketal formation.


  1. N. P. McLaughlin, P. Evans and M. Pines, The Chemistry and Biology of Febrifugine and Halofuginone, Bioorg. Med. Chem., 2014, 22, 1993.
  2. S. Smullen and P. Evans, Asymmetric Syntheses of Febrifugine, Halofuginone and their Hemiketal Isomers, Tetrahedron, 2017, 73, 5493.
  3. P. Fischer, M. Morris, H. Müller-Bunz and P. Evans, Synthesis and Structural Elucidation of 1,2- Disubstituted 3-Fluoropiperidines, Eur. J. Org. Chem., 2020, 1165.


Chemical Synthesis of Drug-Like Building Blocks Using Continuous Flow Reactors

Discipline: Chemistry
Supervisor: Dr Marcus Baumann, School of Chemistry

We wish to offer this unique summer research project that will provide a talented student with the opportunity to acquire novel laboratory skills in a project at the interface of organic chemistry, medicinal chemistry and chemical engineering. The synthesis and spectroscopic characterisation of a small collection of drug-like building blocks will be studied. This will involve using bespoke continuous flow reactors available in the newly established UCD Flow Chemistry lab.

Specifically, we will be using a light-driven continuous flow reactor to generate target molecules. Continuous flow chemistry is a novel and exciting addition to the chemist’s toolbox that allows to perform chemistry in a safer, more effective and highly reproducible manner yielding readily scaled and automated processes that are highly desirable in academia and industry alike. This approach will avoid the isolation of unstable intermediates and provides a powerful route into important bioactive structures. Using light as a traceless reagent in combination with in-line purification techniques will result in a green and sustainable technology that highlights the power of modern chemical synthesis in delivering important drug-like structures. The ability to automate this process is highly advantageous as it circumvents tedious downstream processing to yield clean products. The successful student will be embedded in our international research group and gain new skills in chemical synthesis, purification, spectroscopic characterisation as well as the use of modern flow reactor technology. For an example of a past project that was subsequently published, please see:


Hot date in the mountains: determining the magmatic age of the Mourne Mountain Complex, Northern Ireland

Discipline: Earth Science
Supervisor: Dr Paul Slezak

The Mourne Mountains Complex (MMC) is in County Down in Northern Ireland and is a potential rare earth element (REE) resource for Europe. The MMC consists of five (G1-G5) Palaeogene-aged granitoids. Past work on the MMC includes an initial study of granitic magmatism with 40 Ar/ 39 Ar dating on micas and whole rock Rb-Sr dates. However, these results have large uncertainties and no additional, modern-day studies have been completed. Some units, such as the G5 granite, were suggested as being much older than field relationships would suggest. We want to use the latest techniques to add resolution and obtain more precise ages. This study will conduct high resolution, U-Pb dating via laser ablation inductively coupled plasma mass spectrometry (LA-ICP-MS) to determine the precise dates of magmatic emplacement for this mountain range.

As a student, you will take on the role of a research assistant and learn how to approach a geochronologic study. You will learn how to: 1) prepare samples in the lab; 2) analyse samples for U-Pb isotopes; and 3) use the latest data reduction software (e.g., Iolite and Isoplot) to determine the ages of the zircon crytals and ultimately the ages of the different granites. Time permitting, you will also learn about trace elements in zircon and how to use IoGAS to plot geochemical data. You will be included as a co-author in any publications emanating from this work. These geochemical programs are used in both academia and industry, providing you with transferable skills for different career paths.


Determining the age of Irish and European ore deposits

Discipline: Earth Science
Supervisor: Dr. Danny Hnatyshin, Postdoctoral Researcher at University College

The successful exploration for new sources of raw materials requires sophisticated models of mineral deposit formation. A key constraint for developing these models is knowing when a mineral deposit formed and how this may relate to other regional events such as volcanism or tectonic activity. Specifically, this project will target important ore deposits in Ireland and mainland Europe that supply critical metals (e.g., Zn, Cu, Co, etc...) that are used for technology and infrastructure. The goal of this project is to determine the spatial-temporal relationship between similar ore deposits which will be used to refine models of ore formation at the regional/national scale. To date these ore deposits this project will focus on using the rhenium-osmium (Re-Os) radioactive isotope system. This isotope system is chosen due to its unique geochemical properties that allows it to be sequestered into the sulfide minerals that comprise ore deposits. The variety of different aspects of this research project should appeal to a wide audience interested in geochemistry and economic geology. The student could learn about, and assist, in sampling, sample processing (e.g. mineral separation), petrography, in-situ micron-scale sample characterization (e.g. electron microscopy, laser ablation mass spectrometry), clean lab wet chemistry for Re-Os age dating, isotopic analysis using mass spectrometry, or data analysis, depending on their desires or skillset.


Optimized design of a Hartmann-Shack wavefront sensor for ophthalmic applications

Discipline: Physics
Supervisor Assoc. Prof. Brian Vohnsen

With this project we aim to determine an optimized design of a lenslet array and camera to sense ocular aberrations with high accuracy and low noise. We will develop coding for centre-of-mass centroiding and Zernike polynomial reconstruction, and determine optimal parameters to discriminate against noise and corneal reflections. The sensor will be validated experimentally using a microlens array and its performance will be compared to that of existing Hartmann-Shack sensors with respect to dynamic range and accuracy when sensing ocular aberrations in real time. Ultimately, this type of sensor may be implemented to evaluate both foveal and peripheral ocular aberrations and used for sensing of high myopia and eyes with compromised vision.

The following information is vetted and provided by the American Association of Collegiate Registrars and Admissions Officers (AACRAO) on the Electronic Database for Global Education (EDGE).

Letter Grade Percentage Ranking U.S. Equivalent
A+/A/A- 70 - 100% First Class Honours A
B+/B/B- 60 - 69% Second Class Honours Upper B+
C+/C/C- 50 - 59% Second Class Honours Lower B
D+ 45 - 49% Third Class Honours C+
D/D- 40 - 44% Pass C
F 0 - 39% Fail F
Intellectual property copyright AACRAO EDGE