What you need to know
Duration: 6 weeks
When: Any 6 weeks between 12th May – 14th Aug (You decide what works best with the supervisor)
How much will you get paid: €350 per week !!!!!!!!!
Who is eligible? Any undergraduate student from an under represented group (Male or female) including but not excluded to females, refugees, traveling community etc
Where to apply: To apply for an internship, click here
Application Deadline: Sunday 3rd April
Anything Else? There will be a poster presentation of your project in September 2022
Please apply to any and ALL internships that interest you, even if you aren’t from that department/area of STEM!! If you are trying a different area, explain why in your cover letter (eg you have a passion for programming, want to do a masters in that area etc…)
Biomedical Engineering (1)
Title: Identification of sub-phenotypes of intervertebral disc degeneration in human disease.
Supervisor: Prof. Abhay Pandit
Description: Low back pain (LBP) is the second leading cause of disability with global prevalence and is primarily caused by the degeneration of the intervertebral disc (IVD) resulting in the compression of the spinal nerves and adjacent vertebrae. The real-world effect of degenerative IVD has a remarkable socio-economic impact and associated healthcare expenditure is estimated at over 100 billion dollars annually in the USA and €5.34 billion in Ireland alone. While IVD degeneration typically affects older people, younger patients also present with severe disc pain. Current therapy for IVD degeneration focuses on spinal fusion devices, which aim to alleviate pain through the removal of a damaged or diseased disc. While this approach has proven clinical benefits, many patients do not respond to this treatment and remain with chronic pain. Given the lack of satisfactory outcomes in treatment strategies for IVD degeneration, it is clear that new molecular targets need to identify at-risk patients and to halt disc degeneration, restoring native tissue structure and function. Previous projects on IVD profiling revealed variable molecular signatures in patients undergoing discectomy. This project aims to further profile these discs and use molecular markers to identify patients at risk of disease and identify new targets for disease intervention. Sub-classification of patients using these precision medicine techniques will likely determine individual responses to future molecular-based therapies to provide patients with better outcomes.
Biomedical Engineering (2)
Title: An implanted device to improve heart function in heart failure
Supervisor: Dr. Eimear Dolan
Description: Heart failure is a medical condition where the heart does not work as efficiently as it should. In this project the student will use Engineering principles to design and develop an implanted device that aims to improve heart function in heart failure. Within this project, methods could include reviewing scientific literature, engineering analysis (e.g beam bending), mechanical characterisation of materials, fabrication and testing of prototypes.
Electrical & Electronic Engineering
Title: Investigation of interference between wireless power transfer systems and surrounding metal regions
Supervisor: Dr. Maeve Duffy
Description: Wireless power transfer is widely used in battery charging systems ranging from applications in mobile phones to electric vehicles. During wireless power transfer, electromagnetic fields produced on the transmitter side link with inductive coils on the receiver side to transfer power between them. However, In addition to linking with the receiver coil, the electromagnetic fields link with surrounding metallic regions such as enclosures and chassis regions, and even with the batteries themselves. This project will apply electromagnetic modelling techniques to determine the extent of this issue and to investigate methods for overcoming it. It will involve Finite Element Analysis modelling, wireless power transfer circuit design, build and test, and the development of related demonstration materials suitable for use in teaching and outreach.
Civil Engineering (1)
Title: Future Feeds – Exploring Computationally Assisted Formulation for Sustainable Animal Feeds
Supervisor: Dr. Ronan Cooney
Description: The proposed placement will allow the student to gain experience in a transdisciplinary research setting, in an active, emerging sustainability research cluster. The student will be supported by research and academic staff from natural science, computer science and civil engineering. This research setting will expose the student to the multidisciplinary nature of modern research programmes and allow them to gain, knowledge and experience in topics such as machine learning, life cycle assessment, nutrition, and process optimisation. The student will work primarily on the development of a training dataset for development of a prototype multi-objective machine learning model that will balance a number of criteria (e.g., nutritional composition, environmental footprint, ingredient costs) to design sustainable animal feeds. This will allow the student to develop sought-after skills for potential future careers in topical areas such as aquaculture, animal nutrition, sustainability assessments and machine learning. The work will be tailored to the student’s primary career area so as to provide them with valuable experience, while also partaking in multidisciplinary activities.
The internship will be held in the Alice Perry Engineering Building, where the successful student will be trained in different aspects of the research project i.e., water quality analysis, environmental modelling and multi-objective decision making. The student will also visit on-site research at MRI Carna for further experience in ongoing research projects on fish husbandry and nutrition. The student will also be encouraged to produce an article on their research outputs for industry magazines (i.e., All About Feed, Aquafeed International), participate in writing a research manuscript for a journal such as Animal Feed Science and Technology, or to submit an abstract to a relevant conference (i.e., Environ, ICES Dublin 2022, European Conference on Artificial Intelligence). With this opportunity, the student will be trained to have the necessary skills to pursue further studies or enter the marine sector, e.g., aquaculture.
Civil Engineering (2)
Title: Sustainable & Resilient Structures and Buildings
Supervisor: Prof. Jamie Goggins
Description: Apply leading-edge scientific and engineering methods to develop the improved infrastructure and built environment required for sustainable social and economic development. We have a strong history of collaboration with industry and international research institutes. The intern would work closely with a research team on one of our collaborative projects. Topics include: renewable energy (in particular tidal energy, wind energy and wave energy technology); sustainable construction; effectiveness of technologies for retrofitting existing buildings, regarding their structural, environmental and energy performance, and their influence on health, safety and comfort of building users.
Civil Engineering (3)
Title: Structural testing of tidal turbine blades
Supervisor: Dr. Will Finnigan
Description: The intern will work closely with the Project Team for the H2020 CRIMSON Project as they test a full-scale tidal turbine blade during Summer 2022. The structural testing of the blade will take place in the Alice Perry Engineering Building but some aspects will be done remotely. The device has been developed by ORPC and a prototype is currently in operation in Alaska.
Energy Systems Engineering
Title: The role of green hydrogen in Ireland’s energy transition
Supervisor: Dr. Rory Monaghan
Description: The UROP will support the work of a number of large-scale hydrogen projects currently being led by NUI Galway researchers, including the Galway Green Hydrogen Hub (G2H2) and HyLIGHT. You will work with industry partners to develop their understanding of how hydrogen fits in their decarbonisation strategies.
Title: Artificial Intelligence for Medical Image Segmentation
Supervisor: Dr. Bharat B Tripathi
Description: This project will involve development of artificial neural networks for classification of medical images obtained from the publicly available datasets. Together with a Master’s student, the intern will be involved in exploring the different approaches for building data-pipeline, and strategies for training deep artificial neural network.
Learning gains: Introduction to Linux, Python, Tensorflow, literature-review
Regenerative Medicine Institute (REMEDI)
Title: Characterisation of mesenchymal stem cells in companion animals
Supervisor: Dr. Ana Ivanovska
Description: Veterinary regenerative medicine is an actively growing field, looking into novel therapeutic solutions based on cell products and tissue engineering for treatment of chronic and inflammatory disorders in animal patients.
Our research work and the present project proposal are driven by the initiative One Health – One Medicine, where we look to translate our knowledge and expertise gained on human cell technologies to develop scientifically-driven animal cell therapies. Currently, we are working with equine and canine adult mesenchymal stem cells (MSCs), focusing on methods of characterisation and cell manufacturing that will lead toward the development of a standardized cell product.
The present project will be done in collaboration with the orthopaedic surgery team of ArkVets Galway. They will supply canine adipose tissue samples collected during routine neutering procedures under general anaesthesia following owner consent.
Based on the clinical availability, the student will either process fresh adipose tissue samples and isolate MSCs, or will work with early stage frozen cell samples from our master cell bank.
During this internship, the student will have the opportunity to be actively involved in our routine cell culture laboratory work, and learn the basis of cell technologies and cell characterization protocols based on the morphology, growth abilities and gene expression characterization with PCR. Additionally, the student will actively participate in our weekly group research updates meetings, where they will have the opportunity to learn more about the current advancement in cell technologies with a specific focus on osteoarthritis and advanced cell manufacturing.
The impact of this work is two-fold: it will generate data regarding adult canine MSCs characterisation, currently needed for defining laboratory quality controls, that will translate into standards required for the optimisation of therapeutic protocols in animal patients.
Pharmacology & Therapeutics
Title: Biomaterial-enhanced cellular brain repair for Parkinson’s disease.
Supervisor: Prof. Eilis Dowd
Background: One promising approach for the treatment of Parkinson’s disease (PD) cellular brain repair whereby the cells that have died in the condition are replaced by transplantation of healthy cells into the brain. However, this approach has faced several limitations including poor survival of the transplanted cells in the PD brain. To address this limitation, we have recently shown that biomaterials – that is, materials that have been specifically engineered to interact with living systems for therapeutic purposes – have the potential to dramatically improve cellular brain repair for PD. Specifically, when the brain cells were encapsulated in a growth factor enriched biomaterial before transplantation into the (rat) PD brain, the survival of the cells was dramatically improved, and this enhanced brain repair and recovery of movement control.
Aims: Thus, the aim of this project is to continue and extend these previous findings, and to determine if growth factor enriched biomaterials can also improve cellular brain repair for PD when using a newly discovered source of healthy brain cells that has just entered clinical trials in patients, which are those generated by genetic engineering of human skin cells (so-called induced pluripotent stem cells (iPSCs)).
Study Design: To do so, iPSCs have been converted into the appropriate type of cells for repairing the PD brain (premature dopaminergic neurons) and these have already been transplanted into the (rat) PD brain with or without the biomaterial, and with or without growth factor enrichment. The ability of the cells to repair the brain will be assessed over the course of the summer placement using immunohistochemistry of the brain tissue.
Long-Term Potential Impact: This approach has the potential to dramatically improve movement control in patients with PD by repairing and reconstructing the brain circuits that degenerate in the condition. In these patients, the reconstruction and restoration could provide benefits lasting decades.
Centre for Cell Manufacturing Ireland
Title: Optimisation of media for NK cell expansion, freezing and recovery with the best viability percentage.
Supervisor: Dr. Maryam Sakhteh
Description: In CCMI (Centre for cell manufacturing Ireland), we are manufacturing Advanced Therapy Medicinal Products (ATMPs). The main activity here is to provide stem cell products for several clinical trials in addition to R&D projects on engineered Natural Killer cell (NK cell) therapy, which has broad applicability across a wide range of targets and tumour types.
The proposed project for UROP Internship: Optimisation of media for NK cell expansion, freezing and recovery with the best viability percentage.
Plan: NK Cells will be isolated from peripheral blood. Purified using Quadro MACS Separator and seeded in plates with different media types (i.e. RPMI, NK MACS, LONZA X-VIVO). The Cells would be expanded for a few days to achieve 80-90% confluency. Following counting and viability assessment, they will be frozen using different media compositions and serum/DMSO ratios. The recovery would be assessed after at least 5-7days of being frozen, based on count and viability percentage in addition to growth quality.
The candidate will be trained on
• Aseptic handling in routine aseptic cell culture activities
• Cell culture basics and techniques
• NK cell isolation from Buffy coat of peripheral blood cells using Ficol.
• NK cell purification using Quadro MACS Separator and magnetic antibodies
• Manual Cell counting and viability assessment
• Scientific online research, writing and presentation skills
Based on the candidate’s suitability and enthusiasm, they can also go on a tour around the cell production facility.
Title: Mechanisms Underlying Altered Pain Processing in Autism Spectrum Disorder
Supervisor: Dr. Michelle Roche
Description: Autism Spectrum disorders (ASD) are a group of neurodevelopmental disorders characterised by impairments in social interactions, communication and repetitive behaviours. In addition to the core symptoms, ASD is also associated with a host of comorbidities including sensory abnormalities such as hypo- and hyper-sensitivity to touch and painful stimuli. However, it is unknown which changes within the central nervous system may be responsible for the altered touch and pain responding in ASD individuals. This project will use a range of laboratory methodologies to examine if pain pathways are altered in a preclinical model of ASD and if this is different between males and females. Data arising from this project will provide further insight into mechanisms that may underlie altered pain processing associated with ASD and possible novel sex-specific therapeutic targets.
Title: Exploring drivers of deep-sea species diversity
Supervisor: Ms. Alexa Parimbelli
Description: In 2018, we collected 110 hours of video footage of cold-water coral habitats from Ireland’s deep ocean (800-2700 m) using a remotely operated vehicle. In this project, we want to look at how the large benthic corals and sponges affect overall biodiversity by hosting other organisms, which are using them either as a substrate, a shelter, or a food source.
We already created a baseline dataset identifying all the corals and sponges (the hosts) and all the animals living on them (the associates). Through an international collaboration with researchers at Edinburgh University, we now wish to extend this dataset to make it comparable with a dataset from Mingulay Reef, a much shallower cold-water coral habitat (~150 m depth) west of Scotland. Specifically, from the video, the project student will record information on body size, body roughness, texture, orientation, and growth form of the hosts; count the different species of associates found on each host. The data will subsequently be merged with the Mingulay dataset with the aim of producing a scientific publication.
The student will work closely with Alexa Parimbelli, the PhD student who identified the organisms, and will be part of a larger deep-sea research group studying multiple aspects of Ireland’s deep sea, and should gain substantial knowledge of Ireland’s deep-sea during the project.
Earth & Ocean Sciences/Zoology
Title: Evaluating the climate change impact has on European lobster robustness
Supervisor: Dr. Alex Wan
Description: Climate changes have brought significant changes in ocean dynamics and marine life. The adaption to future increases in sea temperature remains unknown for many aquatic animal species. The proposed placement programme is to allow the student to develop the research skills and knowledge capacity to address this question. The student will carry out a trial study on the effects of elevated temperature has on lobster physiology and gut robustness. During the study, the student will work as part of a highly active, international, and friendly team. To address the research question, the placement will involve training in animal husbandry, behaviour, and welfare, water chemistry, aquaculture systems, physiological, histological, biochemical assays, and social and economic impact assessments. Furthermore, the successful student will be encouraged and mentored to write an article on their research outputs for publication in an industry-based journal (i.e., Aquafeed International or Inshore Ireland) or write a peer-review research manuscript to be published in a Q1 scientific journal, such as Nature sustainability, Scientific reports, or Aquaculture. This internship will be based at Carna Research Station and transport will be arranged for the student if needed. In addition, the student would also have the opportunity to participate in other research projects such as collaborating with the Marine Institute’s ASTRA project, which is evaluating the potential of lobsters being part of a sustainable integrated multitrophic aquaculture production system. The placement researcher will develop multi-disciplinary skills and a wealth of knowledge to allow them to be career-ready in the marine sciences or a related discipline. Depending on the trial success and performance, the student will be offered an additional 2-3 months of placement bursary to develop this study to a PhD research study proposal.
Title: MICRO-ENZYME- Mining MICRObiomes for novel Enzymes
Supervisor: Dr. Alexandre de Menezes
Description: In this project, a novel strategy will be developed to enrich naturally interacting microbial groups from soil and freshwater samples followed by functional screening. This will be achieved using micrometre-sized magnetic beads coated with biopolymers, while impregnation of biopolymers with different growth substrates will be used to maximise the diversity of microbial colonisers. The magnetic microspheres, which were recently synthesised in the de Menezes’ laboratory, will allow colonising microorganisms to be sufficiently close to interact in the microsphere surface, triggering the expression of microbial interaction related genes. Microbial interaction will trigger the expression of genes associated with biosynthetic gene clusters normally not active in microbial pure cultures and hence lead to the production of bioactive compounds, including enzymes, which are overlooked in standard screening methods. Magnetism will allow the recovery and manipulation of the colonised microspheres, which will enable high-throughput screening for bioactive-compound/enzyme production. The intern will be involved with method development and will carry out microsphere synthesis and characterization. Microscopy will be used to characterize the microspheres and determine the suitability of different polymers for microbial colonization and DNA sequencing will be used to determine the identity of microbial colonizers.
Title: Hydrogel-Forming Properties of Formylglycine-Containing Short Peptides
Supervisor: Dr. Eddie Myers
Description: Synthetic and naturally sourced water-swollen viscoelastic materials (hydrogels) that can closely mimic the biochemical and mechanical properties of the ECM are crucial for the next generation of healthcare products with applications in wound healing, tissue engineering, drug delivery and bioprinting. Hydrogels derived from natural building blocks, such as peptides and sugars, are likely to have favourable biodegradability and biocompatability. Recently, it has been shown that ultrashort peptides (<7 residues), which could be produced on a commercial scale, can assemble into weak hydrogels that can be strengthened through chemical crosslinking, for example, through disulfide-bond formation. For example, the peptide of sequence LIVAGKC spontaneously assembles into a weak hydrogel, which can be strengthened through the application of hydrogen peroxide, which effects disulfide bond formation. We would like to create libraries of such peptides incorporating formylglycine (or dehydroalanine), which is a biochemically relevant post-translationally produced amino acid derivative. We anticipate that the aldehyde functional group will react with terminal or side-chain amino groups to form imines/enamines and other condensation products, covalent linkages that might strengthen the hydrogel. Furthermore, the propensity to form such linkages could be used to attach cargo to the hydrogel for drug-delivery applications.
The student will prepare a formylglycine (FGly) amino acid derivative for automated peptide synthesis. Together with commercially available Fmoc-protected amino acid derivatives, short peptides (<7 amino acids) of sequences like those that are known to spontaneously form hydrogels (LIVAGKC, LIVAGKFGly) will be prepared by using automated peptide synthesis on a rink amide resin Libraries of peptides will be prepared by using the parallel synthesis capabilities of the instrument. Libraries of control peptides will also be prepared, where the formylglycine derivative is replaced with a series derivative, for example. The peptides will be isolated as white powders and resuspended in buffer. Visual inspection of the resulting mixtures and tube-inversion will allow the identification of promising sequences for strong hydrogel formation. The contribution of the formylglycine residues to hydrogel formation will be ascertained through comparison with the corresponding serine-containing peptides.
The student will learn how to perform multi-step syntheses, analysis, and characterisation, including reaction set-up, maintaining an inert atmosphere, liquid-liquid phase separation, column chromatography, crystallization, NMR, HRMS and HPLC analysis, the operation of a peptide synthesizer, centrifugation, and lyophilization. The student will learn how to properly document data, how to perform risk assessments, and how to present research findings to an audience. The supervisor will interact with the student daily where possible and there will be weekly progress meetings. The student will be allowed to proceed at a pace that is comfortable and that allows a deep understanding of the associated chemical theory. The student will be given the opportunity to make an intellectual contribution to the project by designing appropriate peptide sequences, as guided by recent literature.
Agriculture & Bioeconomy
Title: Genome editing in ryegrass
Supervisor: Dr. Galina Brychkova
Description: Sequenced plant genomes can now be edited using the CRISPR/Cas9 system. In this project, the student will use molecular biology techniques and tissue culture techniques. Student will be involved in plant transformation to alter the sequences of genes involved in important agronomic traits.
- Plant molecular biology
- Crop plant genetic transformation protocols
Title: Bio-mining kingdom Fungi for novel bio-pharmaceuticals
Supervisor: Dr. Maria Tuohy
Description: The project will characterize new fungal isolates using molecular (PCR-based) and classical (culture and microscopy) identification techniques. These isolates will be screened for production of biochemicals (secondary metabolites) with a target biological activity. Specifically, biological activity assays will focus on anti-microbial, antioxidant and cytotoxic activities. The student intern will be a valued member of the research team and will receive training a range of research methodologies and concepts in experimental biochemistry/biomedical microbiology e.g. aseptic techniques and cell culture, microscopy, nucleic acid extraction (DNA and RNA), PCR and relevant bioinformatics approaches, nucleic acid electrophoresis, methods for metabolite analysis, bioactivity screening bioassays, as well as in experimental design, hypothesis-testing, data analysis and presentation, and laboratory safety. As part of their training, the student will be shown how to complete a risk assessment for an experiment in their work programme.
Title: Processing of astronomical images from the Galway Ultra Fast Imager (GUFI)
Supervisor: Dr. Ray Butler
Description: The student intern will install the necessary scientific software environment on their own computer (Astroconda & PyRAF) and then the GUFI data processing pipeline. They will learn how to run the pipeline and calibrate the data. They will process data from sources which vary in their light output, and produce light-curves showing this variation in comparison to surrounding stars. More in-depth analysis can be performed, such as periodicity searches, if the project is proceeding well.
Unit for Linguistic Data
Title: Homophobia/Transphobia Detection in social media comments
Supervisor: Dr. Bharathi Raja Chakravarthi
Description: Student will be provided with sentences in comment, extracted from social. Student should create a deep learning/machine learning model. Given a comments, a model must predict whether or not it contains any form of homophobia/transphobia. The seed data for this task is the Homophobia/Transphobia Detection dataset , a collection of comments from social media. The comments are manually annotated to show whether the text contains homophobia/transphobia.
Computer Science (1)
Title: Generalising from simple images: a task for artificial intelligence
Supervisor: Dr. James McDermott
Description: Here is a simple task that humans can do easily: given a few images, if they have some property in common, we can say what that property is; we can say whether a new image has the same property; and we can create new images with that property. To take a concrete and very small example: in the game Space Invaders, there are three main enemies [https://en.wikipedia.org/wiki/Space_Invaders], each an image about 10×20 pixels. These three images seem to have some properties in common, such as eyes and left-right symmetry.
Current Artificial Intelligence methods can’t do this! But some AI researchers advocate working in very simple domains like this to try to understand the nature of intelligence better [https://github.com/fchollet/ARC].
In this project we will:
- Create very simple rules for testing whether a Space Invader-size image has properties such as eyes, left-right symmetry, up-down symmetry, etc.
- Test these rules on some new images we will create by hand.
- Given the three example images, detect which properties they have in common.
- Create simple methods for generating images.
- Put everything together for an overall system which generates new images and filters for the right properties.
(If you prefer, we can choose some other images instead of Space Invaders.)
The student needs to know basic programming in any language. If you know how to write the function
test_left_right_symmetric(), you are ready to start this project:
x = [ [1, 0, 0, 1], [1, 1, 1, 1], [0, 0, 0, 0], [0, 0, 0, 0] ] test_left_right_symmetric(x) # returns True y = [ [1, 0], [0, 1] ] test_left_right_symmetric(y) # returns False
Computer Science (2)
Title: Ensuring Cyber Hygiene: Attack Vectors Analysis and Mitigation Strategies
Supervisor: Dr. Mamoona Asghar
Description: Cyber/Cybersecurity hygiene is a set of practices that organizations and individuals adopt to maintain the health and security of their users, devices, networks and data.
Data Science Institute
Title: Digitisation and annotation of Old Irish inflected forms
Supervisor: Dr. Theodorus Fransen
Description: The internship will revolve around the collection of inflected forms in Old Irish (ca. 600–900 A.D.) and making these forms available in machine-readable format and according to standard annotation frameworks. Inflection is the process whereby a base form or lemma (e.g., the English verb “go”) changes shape according to its function in a sentence (e.g., The woman goes to the supermarket, The boy went to school, They have gone away). A tabular representation of inflected forms for a particular lemma is known as a (morphological) paradigm, and when multiple lemmas are involved, one speaks of an inflected lexicon. Inflected lexicons are import in computational morphology, a field that investigates how words are formed from smaller bits, or how words should be meaningfully segmented (broken up), and how a computer can assist in automating these tasks.
The collection, digitisation, and annotation of paradigms for Old Irish will assist and inform many Natural Language Processing tasks for this language stage, including building an automatic morphological analyser/generator, and automatically extracting linguistic patterns and changes in the language. A more distant research prospect is the building of digital educational resources focusing on Old Irish grammar. A comprehensive inflected lexicon for Old Irish will therefore be a key addition to resources for this language stage, which still lacks comprehensive digital support and state-of-the-art computational tools.
More specifically and concretely, and depending on personal skills, the successful intern may be expected to work on one or more of the following — increasingly more advanced — tasks:
- Gather inflected forms from Old Irish grammars and text editions as well as (digital) lexicographical resources, convert this data into machine-readable format (if not already available as such), and provide suitable metadata (e.g., textual source, date);
- Convert the machine-readable inflected forms into a database, adhering to a specified database scheme and according to strict annotation guidelines for inflected lexicons;
- Explore further uses of Old Irish paradigms/an inflected lexicon, e.g., integration with the UniMorph scheme/project  and employment of the data for educational applications for historical languages .
The candidate would ideally be familiar with — or at least interested in — one or more of the following topics:
- The Irish language (Gaeilge), either the contemporary language or historical stages;
- Linguistics/grammar and/or (foreign) languages;
- Basic programming concepts (ideally implemented in Python) and/or database creation (e.g., SQL).
The internship project goals are not entirely fixed at this stage; the task description may be slightly adapted according to needs arising on the part of the host, as well as experience/areas of interest on the part of the intern.
In a wider sense, the envisaged project tasks relate to language resources and digitally under-represented languages, as such showing many intersections with the work already being undertaken in the Unit for Linguistic Data (ULD) in the Data Science Institute (DSI), particularly the Cardamom project . The intern will therefore be exposed to a stimulating, interdisciplinary research environment and is encouraged to foster collaborations with researchers in ULD and indeed within DSI.
 Compare, for example, the available apps for ancient and medieval languages at https://www.libphil.ca/