Fundamental Ai Research Scientist - Toronto, Ontario

AstraZeneca

Toronto, Ontario, Canada
Base: 114,333.60 to 150,062.85; bonus/equity: annu...
Fundamental ai research
Deep learning
Reinforcement learning
We are looking for people with both hands-on practical experience and deep theoretical knowledge in fundamental research areas such reasoning, causal inference, deep learning, reinforcement learning, world models, non-convex optimisation, statistical inference, probability theory, computational geometry, multi-task learning, representation learning, multi-scale modelling, multi-property optimization, natural language processing, control theory, meta-learning, category theory, complex systems, statistical mechanics, information theory, knowledge representation, search and optimisation, transfer learning, probabilistic programming, computational linguistics,, and geometric methods

Job Summary

  • We are looking for people with both hands-on practical experience and deep theoretical knowledge in fundamental research areas such reasoning, causal inference, deep learning, reinforcement learning, world models, non-convex optimisation, statistical inference, probability theory, computational geometry, multi-task learning, representation learning, multi-scale modelling, multi-property optimization, natural language processing, control theory, meta-learning, category theory, complex systems, statistical mechanics, information theory, knowledge representation, search and optimisation, transfer learning, probabilistic programming, computational linguistics,, and geometric methods.
  • Your work will support the next generation of medicines and vaccines at the intersection of AI, biology, and engineering.
  • Join our interdisciplinary Centre for Artificial Intelligence team working on the frontier of AI research for science.

Matching Summary

We are looking for people with both hands-on practical experience and deep theoretical knowledge in fundamental research areas such reasoning, causal inference, deep learning, reinforcement learning, world models, non-convex optimisation, statistical inference, probability theory, computational geometry, multi-task learning, representation learning, multi-scale modelling, multi-property optimization, natural language processing, control theory, meta-learning, category theory, complex systems, statistical mechanics, information theory, knowledge representation, search and optimisation, transfer learning, probabilistic programming, computational linguistics,, and geometric methods.

Salary

Base: 114,333.60 to 150,062.85; Bonus/Equity: Annual Variable Pay Bonus/Short Term Incentive and equity-based long-term incentive; Benefits: Flex Benefits & Retirement Savings Program, 4 weeks’ paid vacation, annual Personal Days or Contract Benefits Program

Skills & Requirements

Must-have

  • Fundamental AI research
  • Deep learning
  • Reinforcement learning
  • Causal inference
  • Statistical inference
  • Probability theory
  • Machine learning techniques
  • Algorithmic development
  • Python programming

Nice-to-have

  • Collaborate with diverse individuals
  • Lifelong learning
  • Creative problem solving
  • Interdisciplinary collaboration
  • Open-source projects
  • Cloud computing environments

Key Requirements

  • PhD in machine learning, statistics, computer science, mathematics, physics, or related discipline OR equivalent practical experience
  • Fundamental AI research and development experience
  • Hands-on ability to implement AI/ML techniques
  • Rigorous scientific methodology application
  • Theoretical understanding and quantitative knowledge
  • Programming experience in Python or other languages
  • Ability to communicate and collaborate effectively

Work Rights

Not specified

Tailored Resume

Cover Letter