Short internship projects

in the Sustainable Systems and Methods lab (SSM)
with Prof. David

Join the Sustainable Systems and Methods lab (SSM) of the Department of Computing and Software at McMaster University, the university with the #1 industry impact world-wide! You’ll have a chance to work with Prof. David on a variety of topics, including software and systems engineering, machine learning, and digital twins.

We’re located in Hamilton, Ontario, Canada 🇨🇦, a fantastic place if you like nature and the outdoors. As life is not only work, you will get a great chance to explore Cottage Country and enjoy the beauties of Southern Ontario.

Niagara falls (45-min drive)
Toronto (45-min drive)
Cottages everywhere


The following is a selection of rather well-defined topics, scoped for 2-3 months of work. Ideal for short internships, e.g., for the Summer term for Canadian students.
Depending on the interest of the student, successful internships might result in open-source contributions, scientific papers, etc.


Energy assessment of simulators
You will contribute to our energy monitoring framework we developed to measure the energy consumption of simulators. You will have a chance to contribute to various methods that decrease the energy requirements of simulators.
Required skills: Python

Software engineering

Digital twin dashboard
You will implement an interactive digital twin dashboard users can interact with, using Dash from Plotly.
Required skills: Python, minimal database knowledge.

Tool support for model-based Robotic Process Automation (RPA)
You will implement a productivity tool that helps model RPA configurations and subsequently, analyze and optimize them. The framework has been presented in this paper (Figure 3).
Required skills: Python, Java (maybe some Eclipse) or JavaScript.

Complex event processing (CEP) with Python
CEP is the technique of identifying complex event constellations on voluminous event stream. You will implement a CEP engine in Python, starting from our seminal work available here.
Required skills: Python.

Contributions to the ReLiS literature survey tool
You will implement either user-facing and back-end features, or machine-learning support in a state-of-the-art literature survey tool.
Required skills: PHP, JavaScript, databases.

Model-driven engineering (MDE)

Contributions to the PROxIMA modeling tool
PROxIMA is a process modeling and simulation framework. It allows a mixed multi-objective optimization of process models for various metrics, including the consistency of the model artifacts passed around the process. You will have a chance to learn about how state-of-the-art engineering tools are architectured.
Required skills: Java, Eclipse.