Sort by
Refine Your Search
-
Category
-
Employer
-
Field
-
, biology, engineering, machine learning / data science, coding. How to apply: This is an Expression of Interest process. To express your interest in applying, candidates must supply the following information
-
biology: How do epigenetic features contribute to the regulation of the genome? We study how chromatin drives specificity for regulating gene expression. You will be dissecting the molecular features
-
Applied mathematics, fluid mechanics, high-performance computer simulations. Full time, fixed term position (3 years) at Hawthorn campus $34,700 per annum (2025 rate) About the Scholarship Higher
-
explore unconventional ideas, develop computer algorithms for data analysis, create new experimental approaches, and apply the technique in areas like biomedicine, materials science, and geology. My group
-
mechanisms and transformer models. Qualifications Bachelor’s degree with First Class Honours (or equivalent) and/or a research master’s degree in computer science, AI or Computer Vision; or an equivalent
-
Swinburne’s strategy draws upon our understanding of future challenges. We choose to build Swinburne as the prototype of a new and different university – one that is truly of Technology, of Innovation and of
-
chemistry. Application process Please send your CV, academic transcripts and brief rationale why you want to join this research project via the HDR Expression of interest form to the project lead researcher
-
) and computer simulation (FEA) Experience in material characterisation and experimental testings Knowledge in impact dynamics Passionate and have interest in pursuing PhD degree. Experience in research
-
structural health monitoring, especially on computer vision, image processing, machine learning, deep learning, signal processing and data analysis techniques, are preferred. Application process To apply
-
publications and research experiences in structural dynamics and structural health monitoring, especially on computer vision, image processing, machine learning, deep learning, signal processing and data