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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
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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
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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
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. • 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
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expertise in research methodology or willingness to learn. Well-developed computer skills. Application process Expressions of interest are invited to be submitted electronically to Professor Judith Finn via
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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
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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
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informatics. Research strengths include intelligent systems, data analytics, cybersecurity, digital health, sustainability and human–computer interaction. The Faculty of IT at Monash University provides
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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
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/scholarships Be inspired, every day Drive your own learning at one of the world’s top 80 universities Take your career in exciting, rewarding directions About the project We’re thrilled to announce a unique