Sort by
Refine Your Search
-
Listed
-
Category
-
Program
-
Employer
- University of Toronto
- University of British Columbia
- McGill University
- University of Saskatchewan
- Canadian Association for Neuroscience
- Universite de Sherbrooke
- University of Waterloo
- BioNano Lab
- Institut national de la recherche scientifique (INRS)
- Mount Allison University
- Nature Careers
- Ryerson University
- Simon Fraser University
- 3 more »
- « less
-
Field
-
, molecular properties, and pathological images. Strong knowledge and experience in data science algorithms, methods, and analysis techniques. Experience in programming using Python and R languages and working
-
. Familiarity with omics approaches, including genomic, transcriptomic, and metabolomic analyses. Experience with developing and applying machine learning algorithms to analyze biological data. Application
-
. Responsibilities include (but not limited to): Lead the development of the NC-ARPES technique (hardware, post-processing algorithm, theory, data interpretation) Propose and perform new TR-ARPES studies of quantum
-
will also have the opportunity to contribute to algorithm development, software architecture design, and software implementation. The ideal applicant for this position will have several characteristics
-
; or the training of a machine learning algorithm to read a digitized document written in an under-resourced language. Position description: The University of Toronto Libraries seeks a highly organized, flexible, and
-
: Computer Architecture Algorithms and Optimization Health Research Human-Computer Interaction Machine Learning and ML Foundations Machine Perception Natural Language Processing (including Information
-
in Curriculum Studies (PhD) Teaching in the age of algorithms: Resisting the algorithmic order through co-created sociotechnical experiments Neha Suvindran Doctor of Philosophy in Biomedical
-
software and languages, such as SAS/R/Stata, to explore data validity, develop research variables/algorithms/flags, create analytic cohorts for each study, create sub-cohorts for trainee-led analyses, and
-
, and explainability; developing unbiased algorithms and responsible data use; addressing the social impacts of AI and IT-induced biases; equitable compensation policies; combating labour discrimination
-
and improve performance Conducting neural recordings and stimulation in behaving monkeys. Programming in MATLAB or Python for data analyse Adapt and improve the machine-learning algorithm to the new