Sort by
Refine Your Search
-
Listed
-
Category
-
Program
-
Employer
- University of British Columbia
- University of Toronto
- McGill University
- Dalhousie University
- University of Saskatchewan
- University of Waterloo
- BioNano Lab
- Carleton University
- Institut national de la recherche scientifique (INRS)
- Nature Careers
- Ryerson University
- Simon Fraser University
- University of Guelph
- 3 more »
- « less
-
Field
-
(AC) at the University of Toronto (U of T) is leading a transformative shift in scientific discovery that will accelerate technology development and commercialization. The AC is a global community of
-
(AC) at the University of Toronto (U of T) is leading a transformative shift in scientific discovery that will accelerate technology development and commercialization. The AC is a global community of
-
(AC) at the University of Toronto (U of T) is leading a transformative shift in scientific discovery that will accelerate technology development and commercialization. The AC is a global community of
-
. 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
-
platforms like quantum computers, and writing the algorithms that power machine learning, big data analytics, and predictive modeling. Beyond technological development, SFU’s researchers also explore
-
University of British Columbia | Northern British Columbia Fort Nelson, British Columbia | Canada | 2 months ago
on developing mathematical models and control theory tools to support sustainable fisheries management. The project will optimize fishing practices to reduce ecological impacts, providing actionable insights
-
self-help tools, training programs, and customer workshops to promote meaningful outcomes related to utilization of Bionano tools. Collaborate with product development teams and share critical product
-
: Machine learning/deep learning model development for biomolecular data analyses and prediction Research Area: Data science and computational chemistry Required Skills: A Ph.D. in relevant field within
-
with expertise in biology, biotechnology, computer science, microscopy and bio-engineering that is developing new microscopy hardware and new computational algorithms for the encoding and decoding
-
’ histories, materials, structures, texts, and accretions over time through the application of technologies and methods developed in the natural, computational, conservation and other sciences. Examples might