Sort by
Refine Your Search
-
Listed
-
Category
-
Country
-
Field
-
/internship opportunities in laboratory or field settings; Experience teaching analytical chemistry, instrumental chemistry or toxicology; Ability to teach Bayesian or inferential statistics at the graduate
-
-based, Bayesian or matrix factorization methods for multi-omics integration. Ability to independently perform data analysis and scientific interpretation based on omics data at an internationally
-
, sampling, inference, and machine learning. On one side, statistical approaches such as Bayesian inference play a critical role in identifying the parameters of PDEs, while on the other, newly emerging
-
. • Experience with machine and deep learning modeling approaches and developing Bayesian models. • Multidisciplinary skills to bridge fields such as plant disease ecology, remote sensing data, and geospatial
-
OtherProven ability to demonstrate creativity, innovation and team-working within work Proven ability to work without close supervision Desirable CriteriaExperience with Bayesian statistics Experience working
-
received by November 1, 2025. Preferred skills: Demonstrated experience in modeling and applied statistics including machine learning, Bayesian statistics, multivariate statistics, model assisted estimation
-
- based neural networks, Bayesian statistics, and text analytics are a must. Nice to Have: Experience developing and integrating APIs for healthcare systems to ensure seamless interaction with AI models
-
the admission requirements for a PhD at ETH Zurich Experience in machine learning, optimization, or AI-driven decision-making Preferably with knowledge of Bayesian optimization or Gaussian processes
-
University of Toronto | Downtown Toronto University of Toronto Harbord, Ontario | Canada | 3 months ago
- Population Genetics Course Description: This course introduces students to the genetic variation between and within populations. The topics include evolutionary forces, quantitative genetics, and Bayesian
-
and Bayesian methods. Knowledge of statistical software, particularly R. Strong statistical programming skills. Understanding of clinical trials. An ability to work well both on own initiative and