Sort by
Refine Your Search
-
Category
-
Employer
-
Field
-
materials systems at the molecular level with machine learning. The PhD Student will work with tumour sections to develop multiple instance learning and weak supervision / spatial transcriptomics models
-
Martin Australia invite applications for a project under this program, advancing robotic perception systems through monitoring of their machine learning models. Run-Time Monitoring of Machine Learning
-
interested in connecting spatial and spectral information to understand complex materials systems at the molecular level with machine learning. PhD Student A will work with tumour sections to develop multiple
-
awardee. The Opportunity Generative artificial intelligence is a significant and highly visible use of machine learning which has become commonplace in a matter of a few short years. Without common
-
to $5000 (total) for computer / software / conference attendance to present PhD results. Scholarship Details Maximum number awarded 1 Eligible courses Higher degree by Research (PhD) – in Health Sciences
-
. • be located at the agreed project location(s) and, if required, comply with the university’s external enrolment procedures. Selection criteria Skillset: Proficient in Python, machine learning, and
-
the academic staff at SIT. We are looking for PhD students to work on projects on stochastic optimisation algorithms for hyper-parameter tuning in Machine learning. The successful candidate will explore
-
PhD Opportunity - Indigenous (Energy) Job No.: 685291 Faculty / Portfolio: Faculty of Information Technology Location: Caulfield or Clayton campuses Duration: 3.5-year fixed-term appointment
-
the world. Ideal applicants will have a solid background in AI, machine learning, control theory or quantitative finance. Applicants with advanced programming skills (Python/C++); and a desire to publish in
-
materials systems at the molecular level with machine learning. The PhD Student will undertake a study analysing mass spectral imaging data streams in real time using machine learning workflows. A pathway for