Sort by
Refine Your Search
-
Listed
-
Category
-
Employer
-
Field
-
algorithms and deep learning models. Have proficiency in Python in a Linux environment and development experience using Tensorflow or PyTorch. Have strong linear algebra and computer vision knowledge. Have
-
. This research opportunity will produce policy-relevant, causal estimates of the effects of health preventative interventions on health inequalities. Depending on the student’s interest, potential projects may
-
Computer Systems Engineering ● Materials Science and Engineering ● Mechanical and Aerospace Engineering For further information, please follow the link for each Graduate Research Degree ● 3291 - Doctor
-
and Computer Systems Engineering ● Materials Science and Engineering ● Mechanical and Aerospace Engineering To be eligible to apply for domestic postgraduate research scholarships an applicant must be
-
University under the supervision of Professor Tim Dwyer at Monash University, Australia’s leading computer graphics researcher. Please note that this opportunity is limited to applicants who are legally
-
rules for Marie Skłodowska-Curie grant holders, will consist of a gross annual salary of 28,764 EUR. Of this amount, the estimated net salary to be perceived by the Researcher is 1,926 EUR per month
-
computer vision and machine learning methods to interpret the photovoltaic (PV) solar farm's condition and perform various inspections and anomaly detection. The research will draw from state-of-art
-
condensed matter physics, physical chemistry or biology Possess a strong interest in biological problems using physical and chemical theory and computer-based techniques Meet RMIT’s entry requirements
-
the area of structural health monitoring of civil engineering structures on an Australian Research Council Early Career Industry Fellowship project titled, 'Transforming Smart Bridge Monitoring by Computer
-
Honours degrees in the following disciplines, or with equivalent research or work experience will be favourably considered: Computer and Data Science; Applied Mathematics and Statistics. Number