Sort by
Refine Your Search
-
Listed
-
Category
-
Program
-
Employer
- University of British Columbia
- McGill University
- University of Toronto
- Dalhousie University
- Nature Careers
- University of Saskatchewan
- Universite de Sherbrooke
- University of Waterloo
- BioNano Lab
- Carleton University
- Institut national de la recherche scientifique (INRS)
- OCAD University
- Ryerson University
- SAIT Polytechnic
- Simon Fraser University
- University of Guelph
- 6 more »
- « less
-
Field
-
of Biomedical Engineering, please visit https://www.bme.ubc.ca/ . HuMBL, a research lab within the SBME, specializes specifically in wearable sensor technologies and algorithm-driven health analytics to enhance
-
: Department of Mathematics and Statistics Position Summary : Optimize ML RNN/CNN models on sensor data with healthcare applications. Help interdisciplinary researchers to publish clean codes in public
-
. Key Responsibilities Lead AI/ML algorithm development for predicting plant water and nutrient uptake under varying environmental and growth conditions. Analyze multi-source data, including aerial and
-
network of IoT weather sensors. Assemble, configure, and deploy custom IoT devices in field conditions, including satellite communication modules for remote data transmission. Optimize algorithms for edge
-
data sources such as UK Biobank and eventually come up with algorithm useable for the early detection of Alzheimer’s disease (AD) and Parkinson’s disease (PD). Nature of Work: In this project, we will
-
candidate will support experimental research focused on the synthesis and characterization of photo-activated semiconductor materials. Responsibilities include developing and testing UV-activated gas sensor
-
characterization of photo-activated semiconductor materials. Responsibilities include developing and testing UV-activated gas sensor prototypes, conducting laboratory and field evaluations, and analyzing
-
Science Specialist will: 1) review empirical data and algorithms applied to the price, end-use, fishing effort and layer 3 databases and develop code that imputes missing data to complete gaps in
-
developing machine learning algorithms specifically designed for medical imaging applications. In addition, performs analysis of tissue images of cancer using machine learning methods that have been prototyped
-
and test field protocols for carbon removal tracking and certification Conduct life cycle assessments (LCA) using real-world deployment and sensor data Engage with community partners, carbon credit