Multiple post-doctoral, PhD, and research assistant positions available in the project on "Provably Verified and
Explainable Probabilistic Reasoning," led by the Principle Investigator, Kuldeep S. Meel.
The positions are funded by the 2.5 million dollar NRF Fellowship for AI awarded to PI and additional funding from Defense Service Organization, Singapore.
The project broadly aims to develop of formal
methods for AI techniques and employ advances in AI techniques
for the development of formal methods.
The project is sub-divided into the following four major themes whose detailed
description is available
at MeelGroup Research.
Theme 1: AI for Formal Methods: New Paradigms for SAT, MaxSAT, and Functional Synthesis
Theme 2: Constrained Sampling and
Integration/Counting
Theme 3: Formal Methods for AI: Verification and Testing of AI Systems
Theme 4: Logic for AI: Interpretable Models and Semantically Aware Deep Neural Networks
1. A Ph.D. in CS or related disciplines such as ECE, Mathematics, and OR.
2. Prior publications with deep algorithmic or system contribution in top-tier conferences
3. We work at the intersection of algorithmic design and systems;
therefore, an ideal candidate should have deeper expertise in one area
and willingness to learn the other. A strong background in statistics,
algorithms/formal methods and prior experience in coding are crucial to
make a significant contribution to our research.
Interested candidates should
email meel+postdoc@cs.toronto.edu
with a PDF of CV, which must contain information of at least two
references. Furthermore, a short write up indicating your interest in
a particular theme is required.
The initial term of appointment will be one year extensible for another
year, upon review of satisfactory performance.
The selected candidates will be offered competitive salaries and benefits including generous travel funding to top-tier conferences.
1. A Bachelors/Masters degree in CS or related disciplines such as ECE, Mathematics, and OR.
2. We work at the intersection of algorithmic design and systems;
therefore, an ideal candidate should have deeper expertise in one area
and willingness to learn the other. A strong background in statistics,
algorithms/formal methods and prior experience in coding are crucial to
make a significant contribution to our research.
Interested candidates should
email meel+interns@cs.toronto.edu
with a PDF of CV. Furthermore, a short write up indicating your interest in
a particular theme is required and you should include reviews of two of the papers published in the previous 3 years at AAAI/IJCAI/CP/SAT/CAV conferences. The reviews should be in the body of the email (and not as pdf). Furthermore, the body of your email should contain the phrase: “Here are two papers that I have reviewed”. You should also provide reason for your choice of the papers.
UofT is a world-class university that provides an outstanding and supportive research environment. Its Department of Computer Science is highly ranked (within the top 15) among the computer science departments in the world. Toronto is a vibrant, well-connected city and a research hub in North America.