29 data-"https:" "https:" "https:" "https:" "https:" "https:" "https:" "Dr" "Helmholtz Zentrum Hereon" PhD positions at Queensland University of Technology in Australia
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Machine Learning for Image Classification. Eligibility You must: We would like you to have: sound knowledge of machine learning, computer vision and image processing strong programming skills. How to apply
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sustainable and scalable alternative. The PhD candidate will be supervised by Professor Emilie Sauret, Professor Yi-Chin Toh, and Dr Zhongzheng Wang.
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for admission to a QUT research degree / Doctor of Philosophy . The first step is to email Dr Andrew Stephens detailing your academic and research background, your motivation to research in this field and
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for this scholarship at the same time you apply for admission to a QUT research degree / Doctor of Philosophy. The first step is to email Dr Katharina Esau detailing your academic and research background, your
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students. How to apply Apply for this scholarship at the same time you apply for admission to a QUT Doctor of Philosophy . The first step is to email Dr Daniella Teixeira detailing your academic and
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. First-authored publications on refereed journals is a bonus. How to apply Apply for this scholarship at the same time you apply for admission to QUT's Doctor of Philosophy . The first step is to email Dr
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for the scholarships. Experience in Machine learning and/or finite element modelling would be preferable. The successful candidate will be supervised by Associate Prof. Hafizah Binti Ramli, Dr Sabrina Fawzia, and
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. First-authored publications on refereed journals is a bonus. How to apply Apply for this scholarship at the same time you apply for admission to QUT's Doctor of Philosophy . The first step is to email Dr
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of Philosophy / professional doctorate . The first step is to email Dr Veronica Gray detailing your academic and research background, your motivation to research in this field and interest in this scholarship
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expertise: Bioinformatics experience A PhD student with bioinformatics experience will generate and analyse complex microbiome sequence data to complement existing rumen microbiome datasets. Via multi-omics