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Course Lecturer – Special Topics in Biostatistics (BIOS 691)

McGill · McGill College

New
🇬🇧 English
Bayesian inference Markov chain Monte Carlo Variational inference Monte Carlo integration Sampling importance resampling Gibbs sampler Metropolis-Hastings JAGS Nimble RStan INLA

Job description

About the role

The Department of Epidemiology, Biostatistics and Occupational Health at McGill University seeks a Course Lecturer for BIOS 691 – Special Topics in Biostatistics in the Fall 2026 term. The lecturer will introduce researchers to practical Bayesian methods through a four‑credit course.

Key responsibilities

  • Deliver lectures on Tuesday (10:35 am‑12:55 pm) and Thursday (11:35 am‑12:55 pm) at MC2001, room 1135.
  • Present course topics including Bayesian philosophy, univariate models, linear and logistic regression, hierarchical models, and Bayesian non‑parametrics.
  • Teach numerical techniques such as Monte Carlo integration, SIR, Gibbs sampling, and Metropolis‑Hastings.
  • Guide students in programming with R, JAGS, Nimble, RStan, and INLA.

Required profile

  • MSc or higher in Biostatistics or Statistics.
  • Demonstrated experience in Bayesian inference, Markov chain Monte Carlo methods, and variational inference.
  • Knowledge of Nimble and Stan software.
  • Prior teaching experience in biostatistics or statistics.
  • Authorization to work in Canada and willingness to work in Quebec.
  • Fluent English communication, both verbal and written.

Required skills

  • Bayesian inference
  • Markov chain Monte Carlo (MCMC)
  • Variational inference
  • Monte Carlo integration
  • Sampling importance resampling (SIR)
  • Gibbs sampler
  • Metropolis‑Hastings algorithm
  • R programming
  • JAGS
  • Nimble
  • RStan
  • INLA

Questions fréquentes

Le salaire n'est pas communiqué publiquement par le recruteur. Vous pouvez postuler et négocier directement avec McGill.
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Source : ats:workday

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Published 2 hours ago

Expires 1 month from now

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McGill

McGill College