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Faculty of Science and Engineering

Institute of Data Science

Founded in 2017, the Institute of Data Science (IDS) is committed to research in data science and artificial intelligence, collaborating across disciplines, institutions, and sectors. The goal of our research is to accelerate scientific discovery, improve clinical care and well-being, and to strengthen communities. We specialise in machine learning, decentralised applications related to biomedical data, as well as promoting the FAIR (findable, accessible, interoperable, and reusable) principles. With FAIR as a foundation, we have an emerging focus on responsible data science by design.

Read more about responsible data science by design at IDS.

Fast facts

  • focused on responsible data science by design
  • interfaculty institute
  • fosters a collaborative environment for cross-disciplinary data science research and training
  • develops standards to facilitate navigating the knowledge landscape
  • led by prof. Michel Dumontier
  • hiring for diverse data science positions
Go to the Data Science@UM website

Research

Research at IDS focuses on: 

  • accelerating scientific discovery through powerful platforms for scalable, collaborative and reproducible discovery science
  • improving clinical care and wellbeing by developing a learning health system to understand the health of diverse populations and to maximise the wellness and health outcomes for individuals.
  • empowering communities so that they can learn what works, what doesn’t, and how to enact change to improve the quality of life for themselves and their neighbours

IDS aims to tackle impactful research problems through multidisciplinary teams involving students, researchers, partners, and stakeholders inside and out of the university. We aim to train the next generation of data scientists to be even more collaborative and interdisciplinary.

About IDS

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Prof. Michel Dumontier

Professor Data Science

"Data science offers a solid foundation to examine and understand the world we live in. Importantly, it has never been so easy for young researchers to tackle important issues facing communities using cheap computing power and somebody else's data."

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