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Physics Informed Machine Learning Jobs in Ontario

CMR University

Professor & HOD, Artificial Intelligence & Machine Learning (AI & ML) * HOD, ECE * Assistant ... Basic Sciences (Physics/Chemistry/Mathematics) For details please click on Qualifications and ...

CIBC US

Consultant, Data and AI Scientist

Toronto, ON · Hybrid

... informed decisions. The role performs tasks of technical depth and breadth, utilizing a solid ... You will apply statistical techniques and machine learning models for predictive and prescriptive ...

CIBC

Consultant, Data and AI Scientist

Toronto, ON · Hybrid

... informed decisions. The role performs tasks of technical depth and breadth, utilizing a solid ... You will apply statistical techniques and machine learning models for predictive and prescriptive ...

BMO Capital Markets

Data Scientist

Toronto, ON

CA$82K - CA$154K/yr

Develops prediction systems and machine learning algorithms. Investigates additional technologies ... and risk informed decisions that align to business strategy, protect assets, and adhere to ...

BMO Capital Markets

Associate, Data Engineer

Toronto, ON

CA$90K - CA$120K/yr

Model and design databases and data architectures to support advanced analytics, machine learning ... Qualifications Bachelor's or Graduate degree in Engineering, Computer Science, Mathematics, Physics ...

Td

Data Scientist II

Toronto, ON · On-site +1

CA$81K - CA$115K/yr

Build machine learning models (e.g., XGBoost, regression models) to improve decision-making ... Motivated to constantly strive to find innovative data-informed ways to enhance capabilities * In ...

Td

Data Scientist II

Markham, ON · On-site +1

CA$81K - CA$115K/yr

Build machine learning models (e.g., XGBoost, regression models) to improve decision-making ... Motivated to constantly strive to find innovative data-informed ways to enhance capabilities * In ...

Td

Full Stack Data Science Engineer

Toronto, ON · On-site

CA$120K - CA$154K/yr

... that drive informed decisionmaking. * ML/AI Lifecycle Familiarity : Experience working with ... Solid knowledge of applied Machine Learning, Deep Learning, Large Language Models * Solid cloud ...

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Physics Informed Machine Learning information

What is a physics informed machine learning?

A Physics Informed Machine Learning (PIML) job involves developing AI models that integrate physics-based principles to improve accuracy, interpretability, and generalization. Professionals in this role use machine learning techniques alongside domain knowledge in physics, engineering, or applied sciences to solve complex problems in areas like fluid dynamics, materials science, and climate modeling. Responsibilities often include designing algorithms, implementing simulations, and validating results against experimental or real-world data. Employers typically seek expertise in deep learning, numerical methods, and programming languages like Python.

What are the typical challenges faced by professionals working in physics informed machine learning roles?

Professionals in Physics Informed Machine Learning often encounter challenges integrating complex physical theories with advanced machine learning models, requiring deep domain knowledge and strong technical skills. Balancing model accuracy with computational efficiency and ensuring that models are both interpretable and generalizable can be demanding. Collaboration with domain experts, data scientists, and engineers is common, as projects often span multiple disciplines. Successfully navigating these challenges provides valuable experience and is highly regarded, often leading to further career advancement in research, engineering, or leadership positions.

What are the key skills and qualifications needed to thrive in the physics informed machine learning position, and why are they important?

To thrive in Physics Informed Machine Learning, you need a solid background in physics, strong mathematical and statistical skills, and experience with machine learning algorithms, typically supported by an advanced degree in a relevant field. Proficiency with programming languages like Python, frameworks such as TensorFlow or PyTorch, and familiarity with numerical simulation tools are commonly required. Effective problem-solving, clear communication, and the ability to collaborate with interdisciplinary teams make a significant impact in this role. These capabilities are essential for developing robust, interpretable machine learning models that leverage physical laws to solve complex, real-world problems.

What are popular job titles related to Physics Informed Machine Learning jobs in Ontario?

For Physics Informed Machine Learning jobs in Ontario, the most frequently searched job titles are:

What job categories do people searching Physics Informed Machine Learning jobs in Ontario look for?

The top searched job categories for Physics Informed Machine Learning jobs in Ontario are:

Physics Informed Machine Learning jobs near you
Infographic showing various Physics Informed Machine Learning job openings in Ontario as of August 2026, with employment types broken down into 6% Internship, 37% Full Time, 51% Part Time, and 6% Contract. Highlights an 100% In-person job distribution.

School of Engineering and Technology (SOET) - CMR University

CMR University

Full-time

Re-posted 13 days ago

Job description

CMR University offers an outstanding and comprehensive array of academic programmes, and at the core of our wide range of academic inquiry is the commitment to attract and engage the best minds in pursuit of greater human understanding, pioneering new discoveries, and service to society. If you are a motivated academic or research professional ready to make a difference, CMR University is the right place for you to help change the world. 

About the School of Engineering and Technology (SOET)

The School of Engineering and Technology (SOET) has a built-up space of 2,00,000 Sq. Ft. spread across a sprawling 66-acre campus in North Bengaluru. Students from all parts of the country and abroad are pursuing their graduate studies at SOET. With a balanced staff to student ratio of 1:12 and Outcome-Based Education (OBE) approach with the Choice Based Credit System (CBCS) curricula, we follow innovative teaching and learning paradigms. This includes project-based courses like Python, CAD with rapid prototyping, Making with Electronics and case study based courses like Control Engineering, Entrepreneurship, etc.

 The School of Engineering and Technology (SOET) seeks candidates in all fields for full-time positions. Candidates with accomplished academic credentials are encouraged to apply.

Academic Openings:

  • Professor & HOD, Computer Engineering
  • Professor & HOD, Artificial Intelligence & Machine Learning (AI & ML)
  • HOD, ECE
  • Assistant Professor, CSE
  • Assistant Professor, ECE
  • Assistant Professor, Mathematics
  • Assistant Professor, Statistics
  • Professor of Practice (Software Development) 

 Specialisations:

  • Civil Engineering
  • Computer Science and Engineering
  • Electronics and Communication Engineering
  • Electrical Engineering
  • Mechanical Engineering
  • Information Technology
  • Artificial Intelligence
  • Data Science
  • CAD / CAM Engineering
  • Intelligent Systems
  • Basic Sciences (Physics/Chemistry/Mathematics)

For details please click on Qualifications and Experiences 

Employment Type: FULL_TIME

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