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Postdoctoral Research Associate

2 October 2020
No deadline (Open)
Start Date
1 January 2021 (Negotiable)
David R. Cheriton School of Computer Science,
University of Waterloo,
Waterloo, ON N2L 3G1
Research + Teaching
Tenured Position
Postdoctoral Fellow
Research Fields
We are looking for a postdoctoral research associate to join our research group at the Computer Science department at the University of Waterloo. Our goal is to develop parallel and communication efficient algorithms for large-scale graph-based machine learning.

Example algorithms and applications include but not limited to: optimization algorithms for local graph clustering and optimization algorithms for training graph neural networks for node classification, link-prediction, community detection, graph classification and graph generation.

The successful candidate will also collaborate with the Waterloo-Huawei Joint Innovation Lab and with the end goal to develop a new system or support existing systems on graph-based machine learning. The candidate will also be part of the Scientific Computation Group and the Waterloo Artificial Intelligence Institute.

Starting date: January 1, 2021 or later.

Duration: 1 - 3 years

Salary: $90,000

Additional information can be obtained by contacting Dr. Kimon Fountoulakis by email at

Apply by sending an email to Dr. Fountoulakis following the instructions at

PhD, within the last 3 years, in one of the following or other relevant subjects: numerical optimization, scientific computing, parallel computing, applied math, machine learning.

Knowledge of (randomized) first-order numerical optimization algorithms, numerical linear algebra, neural networks or other machine learning models.

Experience in code development and computational experience in using high-performance parallel computing resources. In particular, demonstrated coding experience in C and/or C++, experience in parallel programming using GPUs and/or using tools like MPI and OpenMP. Experience with neural network frameworks such as PyTorch.

Publication record in high-impact journals, top-tier machine learning, and related conferences.

Excellent written and oral communication skills.
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