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Data Science Phd Jobs in Quebec (NOW HIRING)

AstraZeneca

Medical Science Liaison

Quebec, QC · On-site

Communicating expert opinion, feedback on new data, and clinical trends to Alexion Medical Affairs ... PharmD or PhD or equivalent with experience in biological sciences. Bilingual French/ English.

CellCarta

Scientist, R&D Proteomics

Montreal, QC · On-site

Monitor data quality and take ownership of project execution in the laboratory * Must be capable of working in a Good Laboratory Practice (GLP) environment Education * M.Sc. or PhD in life sciences ...

Gilead

Medical Scientist HIV, Quebec

Quebec, QC

D., PhD are preferred) with 5 years of experience in healthcare or pharmaceutical industry ... Through bold and transformative science, we're driving innovation that has the potential to become ...

AbCellera

Principal Scientist - Toxicology

Montreal, QC · On-site

CA$144K - CA$180K/yr

Providing critical scientific assessment of toxicology data and communicating clear, actionable ... You hold a PhD in Toxicology or a related field, with 8+ years of relevant industry experience ...

Charles River Laboratories, Inc.

Write scientific documents, review and interpret the raw data; * Write, review, and edit stand ... position or PhD in Immunology or any biological related discipline; * Experience in advanced ...

LawZero

Senior ML Research Scientist

Montreal, QC · On-site

Analyze and interpret experimental data in order to steer future research questions and objectives ... Advanced degree in a relevant field (e.g., Computer Science, Mathematics). A PhD is preferred but ...

GlaxoSmithKline

MSL, Respiratory (Quebec)

Quebec, QC · On-site

Advanced degree in a life science, clinical, or medical field (for example MSc, PharmD, MD, PhD) or ... Ability to interpret and clearly communicate clinical and scientific data to clinical audiences.

Mcgill

Research Associate

Sherbrooke, QC · On-site

CA$35.37/hr

PhD in Computer Science, Information Science, or Engineering. * A minimum of five peer-reviewed publications in data mining, machine learning, AI, or cybersecurity. * At least two years of ...

Mcgill

Research Associate

Sherbrooke, QC · On-site

CA$35.37/hr

PhD in Computer Science, Information Science, or Engineering. * A minimum of five peer-reviewed publications in data mining, machine learning, AI, or cybersecurity. * At least two years of ...

LawZero

Senior Distributed ML Engineer

Montreal, QC · On-site

In this role, you will work closely with ML research scientists to solve difficult training and ... An advanced degree (master's or PhD) related to machine learning or distributed ML systems is ...

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Data Science Phd information

What is a data science PhD?

A Data Science PhD is a doctoral-level degree focused on advanced research in data science, which combines elements of statistics, computer science, and domain expertise. Students in a Data Science PhD program typically work on developing new methods for analyzing large datasets, creating machine learning algorithms, and addressing complex problems in areas such as artificial intelligence, data mining, and predictive analytics. Graduates are prepared for careers in academia, research, and industry, where they can lead data-driven projects and contribute to advancements in the field.

What are the key skills and qualifications needed to thrive as a data science PhD?

To thrive as a Data Science PhD, you need advanced expertise in statistics, machine learning, data analysis, and a doctoral degree in a quantitative field. Proficiency in programming languages like Python or R, experience with big data frameworks (e.g., Spark, Hadoop), and familiarity with data visualization tools are typically required. Critical thinking, problem-solving, and strong communication skills help you translate complex data insights for diverse stakeholders. These skills are vital for driving innovative research, making data-driven decisions, and contributing impactful solutions in data-centric environments.

What are some common challenges faced by data science PhDs when transitioning from academia to industry roles?

Data Science PhDs often encounter challenges such as adapting to the faster pace and collaborative nature of industry projects compared to academic research. In industry, there is a greater emphasis on delivering practical solutions within tight deadlines and working closely with cross-functional teams like engineering and product management. Additionally, data science work in industry may require balancing technical rigor with business impact, often prioritizing actionable insights over exhaustive analysis. Building strong communication and stakeholder management skills can help ease this transition.

What can I do with a data science PhD?

A data science PhD prepares individuals for advanced roles in research, analytics, and machine learning across industries such as technology, finance, healthcare, and academia. Graduates can work as data scientists, machine learning engineers, research scientists, or data analysts, often utilizing programming languages like Python or R and tools such as TensorFlow or SQL. The degree also enables roles involving complex data modeling, statistical analysis, and developing innovative data-driven solutions.

What are popular job titles related to Data Science Phd jobs in Quebec?

For Data Science Phd jobs in Quebec, the most frequently searched job titles are:

What job categories do people searching Data Science Phd jobs in Quebec look for?

The top searched job categories for Data Science Phd jobs in Quebec are:

Data Science Phd jobs near you
Infographic showing various Data Science Phd job openings in Quebec as of August 2026, with employment types broken down into 1% As Needed, 84% Full Time, 12% Part Time, and 3% Contract. Highlights an 82% Physical, 4% Hybrid, and 14% Remote job distribution.

ML Research Scientist (probabilistic inference)

LawZero

Montreal, QC • On-site

Full-time

Medical, Retirement, PTO

Re-posted 4 days ago

Job description

We are seeking a Machine Learning (ML) Research Scientist to join our team working on a novel AI safety research agenda. In this role, you will develop and evaluate probabilistic inference methods, with a focus on amortized inference, translating theoretical insights into practical implementations.

Key responsibilities

  • Develop amortized inference methods suitable for high-dimensional discrete and continuous distributions.
  • Develop parameter- and structure-learning methods for large probabilistic graphical models that benefit from amortized probabilistic inference.
  • Design evaluation strategies for methods that rely on probabilistic inference.
  • Collaborate with mathematicians on theory related to learning and inference in probabilistic models.
  • Translate theoretical proposals into high quality implementations in a programming language such as Python.
  • Analyze and interpret experimental results to steer future research directions.
  • Communicate complex findings effectively to various stakeholders.

Skills and qualifications

  • Advanced degree in a relevant field (e.g., Computer Science, Mathematics). A PhD is preferred but not required if the candidate demonstrates exceptional abilities.
  • A minimum of 3 years of experience in deep learning research.
  • Expertise in probabilistic inference is required, in addition to expertise in one or more of the following:
    • Bayesian inference
    • Sampling-based approximate inference methods
    • Amortized inference methods (including variational inference methods or Generative Flow Networks)
    • Parameter- and/or structure-learning in probabilistic graphical models (including causal models)
    • Reinforcement learning
    • Optimal control
  • Strong background in mathematics.
  • Proven experience in developing and implementing machine learning models.
  • Proficiency in programming languages such as Python, and experience with  ML frameworks like PyTorch or TensorFlow.
  • Excellent analytical and problem-solving skills, with a demonstrated ability to think critically about complex systems.
  • Strong communication skills, both written and verbal, with the ability to explain complex ideas to diverse audiences.
  • Track record of contributing to high-quality research in probabilistic inference or related fields.
  • Ability to work collaboratively in a team environment while also being self-motivated and independent.

What we offer

  • The opportunity to contribute to a unique mission with a major impact.
  • Comprehensive health benefits.
  • A minimum of 20 days vacation per year upon start.
  • A minimum retirement savings employer contribution of 4%.
  • Generous flexible benefits designed to contribute to your well-being.
  • A team of passionate experts in their field.
  • A collaborative and inclusive work environment with offices in the heart of Little Italy, in the trendy Mile-Ex district, close to public transportation.

Apply