Sort by
Refine Your Search
-
Listed
-
Category
-
Employer
- Curtin University
- RMIT University
- Monash University
- University of Adelaide
- Queensland University of Technology
- Swinburne University of Technology
- Flinders University
- La Trobe University
- University of Southern Queensland
- Murdoch University
- Nature Careers
- University of Melbourne
- CSIRO
- Data61 PhD Scholarships
- James Cook University
- The University of Newcastle
- 6 more »
- « less
-
Field
-
Multiple PhD Scholarships available - Cutting-edge research at the frontiers of Whole Cell Modelling
to test those predictions. By comparing model forecasts with genomic and phenotypic data from the evolving populations, you will test whether a deep understanding of the cell can inform predictions
-
The PhD candidate will gain intensive knowledge in innovative processing protocols for chemical sensing and to develop data acquisition system with the Machine Learning (ML) and/or Deep Learning (DL
-
The successful applicant will conduct research to design and develop novel machine/deep learning based trust technologies for securing IoT services/devices. The successful applicant will conduct
-
and hands-on experience with AI and computer vision. Solid programming skills in Python, especially with PyTorch. Practical experience with deep learning projects, including working with attention
-
the following knowledge and/or experience are highly preferred: Computer Vision, Signal Processing, Machine Learning knowledge and/or; Experience Industry knowledge and/or; A track record of published
-
are learning more and more how it relates to human health and disease. The new generation of deep metagenomic sequencing, consists in simultaneous sequencing of multiple microbial genomes at once and has
-
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
-
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
-
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
-
, especially in ultracold quantum gases or condensed matter theory Proven analytical, computational, and modelling skills Experience with numerical simulations of quantum or many-body systems A deep curiosity