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Dalhousie's Faculty of Computer Science offers competitive funding to qualified graduate students and is committed to promoting excellence in research and teaching.

We have a diverse group of award-winning professors working in interdisciplinary research across five core areas: Big Data Analytics, Artificial Intelligence & Machine LearningHuman-Computer Interaction, Visualization & GraphicsSystemsAlgorithms & Bioinformatics, and Computer Science Education.

We are pleased to highlight a few of this year's funded fellowship opportunities available to incoming Master of Computer Science and PhD students

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Advanced Algorithm Design for Inferring Evolution

Phylogenetic “family trees” are a primary tool used for studying evolution such as the spread of antibiotic resistant bacteria or transmission of COVID-19. As we collect more and more sequencing data we need better algorithms to infer and compare phylogenetic trees. The successful applicant will design and implement new algorithms and data structures based on graph theory or statistical models for complex problems and big data challenges. The ideal candidate has a strong interest in algorithm design and analysis, graph theory, or bioinformatics. Up to two positions are available, please see https://web.cs.dal.ca/~whidden/positions for more information.

Express your interest in working with Dr. Chris Whidden.

# Novel Metagenomic Approaches to Inferring the Evolution of Infectious Diseases

Metagenomics is the sequencing the DNA from an entire microbial community at once. This type of data is used to try to understand and prevent the spread of antibiotic resistance and diseases such as COVID-19.  Metagenomic data is big, fragmented, and noisy so presents distinct algorithmic challenges.  The successful applicants will develop new software based on graph theory, machine learning, and model-based optimisation to systematically map patterns of evolution in clinical/public health datasets.  The ideal candidate has a strong interest in bioinformatics, graph theory, and working with clinical and government collaborators.

Express your interest in working with Dr. Finlay Maguire.

Speed-up Editing of CIDOC-CRM and Other Such Ontologies

CIDOC-CRM is a Semantic Web (RDFS & OWL) computer ontology for representing artworks. Updating CIDOC-CRM is an active and international effort. Most of the people working in the field are not computer scientists. They would benefit greatly from tools to speed-up the editing and updating of the descriptions. There is also the potential for tremendous benefits from recognizing common patterns in the structure of the descriptions. Those benefits would go well beyond memory institutions (galleries, museums, archives, etc).

This would be a co-supervsion.

Express your interest in working with Dr. Jamie Blustein.

Algorithms and Data Structures

Algorithms and data structures, especially fast and space-efficient algorithms and data structures, including succinct data structures, string algorithms and text indexing, I/O-efficient algorithms, implicit data structures, and adaptive algorithms.

Express your interest in working with Dr. Meng He.

Computational Geometry

Computational Geometry, especially efficient algorithms and data structures for computational geometry.

Express your interest in working with Dr. Meng He.

Algorithms for Studying the Evolutionary Relationships Between Sets of Species

ONGOING PROJECT: This project focuses on the theory and implementation of algorithms for studying the evolutionary relationships between sets of species. These relationships are captured in the form of distance measures between evolutionary trees or in the form of networks that represent the events that may have happened to produce a given set of species. Computational biologists use such comparisons in tools to study the emergence of antibiotic resistance in bacteria, tools to manage biodiversity or tracking the spread of diseases. The underlying algorithmic problems are NP-hard but can be solved efficiently using approaches from fixed-parameter tractability. Developing such parameterized algorithms for comparison of phylogenetic trees and for phylogenetic network construction are the core focus of this project.

Express your interest in working with Dr. Norbert Zeh.

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Artificial Intelligence for Neuroimaging

The Ph.D. student will be involved in the design of techniques for the analysis of imaging problems with a focus on clinical MRI. The aim is to improve the research methods used in clinical practice through the use of machine learning, computer vision, and visualization techniques. All possible projects must have a methodological/computational component and a medical application. For detailed information read here: https://web.cs.dal.ca/~carlosh/positions.html

Express your interest in working with Dr. Carlos Hernandez Castillo.

Forecasting in the Context of Data from Sensors in the Aquaculture Industry Farms

My research revolves around the general area of Data Science, with a strong focus on Predictive Analytics for data with spatial, temporal or spatiotemporal dependencies. Recently, I’ve been focusing my work on modelling rare events, with applications to fraud detection, prediction of extreme values and monitoring activities for anticipating anomalous behavior. I love to see my research being applied and thus I try to maintain a network of collaborations with researchers from other areas.

Express your interest in working with Dr. Luis Torgo.

Machine Learning for Non-speech Audio Processing and Generation

I am looking for extremely strong students for (1) machine learning projects on non-speech audio processing and generation, and (2) machine learning projects related to computational creativity. Both of these are are ongoing themes in my research lab. Students must have an exceptional demonstrated background in math and machine learning, and a strong demonstrated background in audio signal processing or in a creative field (e.g. music).

The accepted student(s) will be part of the Vector Institute and will also have the opportunity to interact and collaborate with health-related ML projects as well.

Express your interest in working with Dr. Sageev Oore.

Machine Learning Related to Computational Creativity

I am looking for extremely strong students for (1) machine learning projects on non-speech audio processing and generation, and (2) machine learning projects related to computational creativity. Both of these are are ongoing themes in my research lab. Students must have an exceptional demonstrated background in math and machine learning, and a strong demonstrated background in audio signal processing or in a creative field (e.g. music).

The accepted student(s) will be part of the Vector Institute and will also have the opportunity to interact and collaborate with health-related ML projects as well.

Express your interest in working with Dr. Sageev Oore.

AI in Healthcare

The research area is "AI in healthcare", focusing on both data-driven and knowledge-driven AI methods applied to a range of health related projects. The students will work in the general areas of (a) machine learning and deep learning for health data analytics; and (b) semantic web and knowledge graphs for health knowledge management. The research themes include clinical decision support system, activity recognition for virtual care, semantics driven literature analysis, and digital health/health informatics. Our research is interdisciplinary where we have strong collaborations with a number of medical specialities.

Express your interest in working with Dr. Syed Abidi.

Real-valued Evolutionary Optimization

I am seeking applications for two Ph.D. positions with a focus on real-valued evolutionary optimization. The aim of the research is to contribute to the design of capable black-box optimization strategies through an understanding of algorithm properties on simple test problems. Areas of focus include constrained optimization, surrogate model assisted evolutionary computation, and evolutionary optimization and machine learning. A strong background in continuous mathematics is an important asset.

Express your interest in working with Dr. Dirk Arnold.

Combining Visual and Acoustic Data for Advanced Analytics Mapping of Seafloor and Change Detection

I have two major streams in my research and are looking for one PhD student for each of them. Generally one is in the area of machine learning applications, the other is in computational neuroscience. 

Express your interest in working with Dr. Thomas Trappenberg.

Neurobiological Models of Hippocampal Correlates of Bipolar Decease

I have two major streams in my research and are looking for one PhD student for each of them. Generally one is in the area of machine learning applications, the other is in computational neuroscience. 

Express your interest in working with Dr. Thomas Trappenberg.

Natural Language Processing and Machine Learning

I am looking for candidates interested in natural language processing and machine learning. The current project include application in explainable AI for NLP and financial prediction, NLP and AI in financial prediction, and AI in behavioral analytics.

Express your interest in working with Dr. Vlado Keselj.

High-recall Information Retrieval and Sense-Making of the Results

A common activity in research is retrieving and making sense of relevant documents to a given research question. The researcher starts with a keyword query, scans the results, modifies the query, and repeats the search. Once a sufficient number of documents has been retrieved, the researcher reads the documents and tries to make sense out of them, by forming clusters or topics, highlighting important sentences for the research question, and eventually compiling a review of the relevant literature. Performing all of these tasks manually is very time-consuming. In our research, we explore machine learning and interactive visualization techniques that make efficient use of human effort and enable a researcher to perform these tasks more efficiently.

Status: Ongoing

Express your interest in working with Dr. Evangelos Milios.

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instructional Design, Technologies, and Systems to Facilitate Learning and Engagement

My research area lies at the intersection of the learning and computer sciences, focusing on instructional design, technologies, and systems to facilitate learning and engagement. The aim of the research is to contribute to the systematic study of teaching and/or learning to address novice programmer misconceptions and other difficulties in introductory programming. The ideal candidate has a strong interest in the development, implementation, and/or evaluation of computing programs, curricula, and courses, as well as syllabi, laboratories, and other elements of teaching and pedagogy.

Express your interest in working with Dr. Eric Poitras.

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Spatial Analysis and Augmented Reality

In this ongoing project we explore how spatial analysis techniques traditionally used in architecture and urban planning can be used to support the authoring, implementation, and evaluation of building-scale immersive augmented reality experiences.  

Express your interest in working with Dr. Derek Reilly.

Positive Pro-social Behaviours in Playful and Gameful Environments

I research Human-Computer Interactions (HCI) for Positive Pro-social behaviours in playful and gameful environments. I research the design, production, and psychology of games. In addition, in my work I have also used games as a test bed to understand humans as they interact in digital online spaces, and digitally augmented physical spaces. I have a passion for ubiquitous computing, Internet of Things, and interdisciplinary research. I work on creating public computing spaces for community benefit and I am an advocate of equity, diversity, and inclusion (EDI) in computer science. 

Express your interest in working with Dr. Rina Wehbe.

VR/AR for Creative Tasks

VR and AR are becoming affordable and accessible for everyday use. One area that has become prevalent is using VR/AR for creative tasks, such as sketching in 3D. This new research project aims to create new adaptive and intelligent user interfaces for 3D design by identifying the actions and elements humans use when thinking spatially. The ideal candidate has a strong interest in VR and AR, HCI and user interface design.

Express your interest in working with Dr. Mayra Barrera Machuca.

Design and Evaluation of Computational Tools for Supporting Artistic Creation in Live Music, Dance, and Other Art-forms

This research encompasses interface design, interactive media synthesis, spatial audio, and collaboration support tools.

Express your interest in working with Dr. Joseph Malloch.

Indigenous Ways of Knowing / Ontologies

Responding to the Truth & Reconciliation Commission's call to represent Indigenous ways of knowing in computer-based knowledge structures

We are working to build a curated collection of non-textual objects. An object is more than the sum of its discrete attributes. To appreciate an object in its full complexity, it must be understood in various contexts—integrating multiple human viewpoints and related resources. The authentic representation of digital and non-textual objects is increasingly an area of concern. The larger project is to develop a multi-faceted interactive curated collection of tangible and archival resources. This work has important implications for oral-historical reconciliation of various communities, such as the transmission of Indigenous ways of knowing, and the digital preservation of cultural heritage.

Express your interest in working with Dr. Jamie Blustein.

Visual Patterns in Artworks and Artefacts

There is currently a global distributed database of art works in galleries. The database is encoded using Semantic Web standards (RDFS & OWL). The database is very limited in what it describes: mostly uncontroversial facts. In combination with other projects about expressing uncertainty in RDF we want to include descriptions of the visual patterns in artworks and artefacts.

This is work with museums and galleries in Nova Scotia and beyond.

Express your interest in working with Dr. Jamie Blustein.

Engagement of Visitors with Artworks

Working with teams at other universities and companies we are trying to make a new way for visitors to experience museums and galleries. Not just to experience exhibits at a distance or have a new way to "access" didactic panels but to interrogate exhibits and have rich discussions with other visitors even if those visitors are not present at the same time.

Express your interest in working with Dr. Jamie Blustein.

Developing User Interfaces (UIs) to Support the Essential Tasks in Computers

We were studying how students and researchers annotated on paper with the intention of developing user interfaces (UIs) to support the essentials tasks in computers. Some work was done in assessing touch-based UIs and some data has not been fully analysed. A deeply interested student could use this as the basis of an excellent PhD thesis

Express your interest in working with Dr. Jamie Blustein.

Tools and Techniques for Scholarly Texts

In HAIKU we are pursuing how to integrate mark making, navigation (place marking), note-taking, annotation, glossaries and to combine them with the ability to seamlessly transclude, version and share documents.

Building on earlier research in HAIKU we are working towards a (semi-)automated system to help users discover information in text and in their existing notes. To create such a system we need to know how to recognize and attach meaning to the marks made by users. A simple example, where our research focus is: which categories, and which marks representing those categories, should be used so re-finding notes is most efficient. We seek to help users to refine their own process so it becomes knowledge-building instead of compiling marks, e.g. "find all text that I've highlighted or circled and then filter for content".

Express your interest in working with Dr. Jamie Blustein.

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Using Machine Learning to Secure IoT Devices

IoT devices such as wearables, voice assistants, and home appliances are becoming an integral part of our lives. However, these devices still represent a security and privacy risk, with large-scale coordinated attacks often populating the news. For example, the Mirai botnet successfully compromised more than 100K IoT devices and engaged them in coordinated DDoS attacks over the last few years. One approach to securing IoT devices is to fingerprint them, i.e., identifying the device type, manufacturer, or event through different forms of traffic analysis. Ultimately, network administrators can use this information to quickly react to threats and/or take preventive measures. In this project, we leverage emerging machine learning techniques to protect IoT devices against security and privacy attacks. On one hand, we seek developing high-speed device fingerprinting appliances that can identify gadgets on-the-fly even on next-generation multi-hundred gigabit networks. On the other hand, we also consider protecting IoT devices against fingerprinting-based attacks from malicious actors (e.g., a man-in-the-middle) by carefully obfuscating their traffic patterns.

Express your interest in working with Dr. Israat Haque.

Accelerating Edge-based IoT Applications

The proliferation of latency and safety-critical applications such as AR/VR, surveillance, autonomous vehicles, and health monitoring has forced service providers to move from the distant cloud closer to users; namely, to edge. The edge computing strives to provide a better quality of experience by seeking faster response times. Our team has been surfing on this new trend by exploring cutting-edge programmable network devices (e.g., programmable switches, SmartNICs) as processing units. The rationale is simple: these devices are closer to the user than any servers. One of our recently developed systems, NetPixel, has shown it is possible to use network switches to classify images with accuracy comparable to traditional servers, all without even reaching out to the latter. This preliminary effort opens up a new field with numerous opportunities. Currently, we are extending NetPixel to encompass convolutional neural network-based classifiers as those are the de facto. In the near future, we envision using NetPixel for processing audio, video, or even network traffic. For further information please check https://pinetdalhousie.github.io/projects/edge.html

Express your interest in working with Dr. Israat Haque.

Crisis Software Engineering / Pandemic Programming

(PhD, MSc, USRA) The COVID-19 pandemic revealed how little is known about how crises, disasters, emergencies and pandemics affect software projects and teams. Yet, many software projects are critical to overcoming crises. The successful applicants will investigate both how crises affect software development and how software professionals can mitigate these effects, with a view toward future crises and climate change.

Express your interest in working with Dr. Paul Ralph.

Sustainable Software Engineering

(Postdoc, PhD, MSc, USRA). The role of software development in sustainability is vastly understudied. Software profoundly affects all three pillars of sustainability: Environmental, Social and Economic. Inversely, the three sustainability pillars apply to every software project. The successful applicants will not only investigate the relationship between software engineering and sustainability but also develop and empirically evaluate tools or practices for improving software project sustainability.

Express your interest in working with Dr. Paul Ralph.

Agile Methods + Human-Centred Design = Dual Track Development

(Postdoc, MSc, USRA) Most software is not very well-designed. Buggy. Unfriendly enterprise systems, insecure websites, predatory mobile games, hate-amplifying social networks, racist AI, and carbon-spewing cryptocurrencies cost us billions, make us miserable and exacerbate the climate crisis. The successful applicants will work with our industry partners to envision and validate better techniques for software design.

Express your interest in working with Dr. Paul Ralph.

Video games + Weights + Cardio + Yoga = Exergaming

(PhD) What if you had to train in real life to level up in your favourite game? That’s the premise of the next generation of exergaming systems. The successful applicant will modify a AAA game to incorporate real life exercise, and develop techniques for recording exercise and measuring player reactions to games. This is a flexible project with a lot of room to focus on your interests, e.g., game design, player studies, biometrics, instrumentation or augmented reality.

Express your interest in working with Dr. Paul Ralph.

Revolutionizing Refactoring with Better Software Metrics

(MSc) Developers continuously reorganize software code to improve its structure (“refactoring”). However, there is no empirically-validated method of measuring structure quality. Instead, refactoring is a completely manual process based on experience, intuition, subjective criteria, and unvalidated professional guidelines. The successful applicants will develop a tool that measures the overall impact of a code change on system organization, and field test the tool with our industry partners. The ideal candidate has a strong knowledge of Java and an interest in software metrics.

Express your interest in working with Dr. Paul Ralph.

Empirical Standards for Software Engineering Research

(PhD, MSc, USRA) Peer review—the foundation of science—is ineffective, unreliable, prejudiced and opaque. It can only be fixed by transitioning to more structured review processes in which reviewers evaluate papers against specific acceptance criteria tailored to a paper’s individual research methodology (e.g. case study, controlled experiment). The successful applicants will create and evaluate tools to facilitate more structured review. The ideal candidate has good knowledge of web programming (e.g. HTML, CSS, Javascript) and an interest in research methods.

Express your interest in working with Dr. Paul Ralph.

Next Generation Software Quality Analysis and Refactoring

Source code analysis, code quality issue identification, and refactoring have been explored extensively in the last two decades. Despite the progress, the existing methods and tools lack efficiency, rigor, extensible support for issue identification, and comprehensive support for potential refactorings. The successful candidate will explore the next generation methods and tools by combining traditional approaches with machine learning-based approaches to improve the state-of-the-art in code analysis and refactoring.

Express your interest in working with Dr. Tushar Sharma.

Bots4SE: Bots for Software Engineering Applications

Software development is complex. The complexity is further amplified by complexity introduced by the domain, scope, large teams, and a variety of development methods, tools, and technologies. The successful candidate will explore the role of automated bots, including conversational bots, to reduce the complexity and improve the productivity of software developers.

Express your interest in working with Dr. Tushar Sharma.