324 computer-engineering-"https:"-"https:"-"https:"-"https:" positions at Monash University
Sort by
Refine Your Search
-
Listed
-
Category
-
Program
-
Field
-
% tuition fee reduction applied annually for the duration of your program for up to 3 years (144 credit points). Number offered Variable based on funding. Selection criteria Awarded based on academic
-
reduction applied annually for the duration of your program for up to 3 years (144 credit points). Number offered Variable based on funding. Selection criteria Awarded based on academic achievement. The 20
-
research at leading international conferences. Indicative total stipend: approximately $54,280+ per annum (tax-free), plus up to $13,265 in travel support and access toEmotiv neurotechnology, computing and
-
People with disabilities are excluded from the assistive technology creation process because the methods and tools that are used are inaccessible. This leads to missed opportunities to create more
-
-disciplinary team of clinician scientists and computer scientists to develop diagnosis/predictive/treatment/robotics surgery models of diseases of interest using multimodal medical data, consisting of images
-
. Demonstrated leadership experience with the ability to lead, coach and coordinate teams to achieve operational objectives. Experience managing budgets, financial administration and reporting. High level computer
-
each year (subject to suitable applicants) one in the Humanities and Social Sciences (HASS) disciplines one in the Science, Technology, Engineering and Mathematics (STEM) disciplines Selection criteria
-
. Required knowledge Strong background in machine/deep learning, computer vision, or applied statistics. Solid programming skills in Python and experience with deep learning frameworks (e.g., PyTorch
-
processes and systems KSC 8: Advanced computer literacy and proficiency in Microsoft Excel and spreadsheet-based data analysis. This criteria is essential. Diversity is one of our greatest strengths at Monash
-
University of Warwick (UK), explores the design and development of computational Decision Support tools to help us better manage the interactions between beneficial insects, such as bees, and the flowering