301 postdoctoral-image-processing-in-computer-science-"Prof" PhD positions in Australia
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engineering, electrochemistry, inorganic chemistry, environmental science, etc., are encouraged to apply. Application process Future student, please contact us via the EOI form . Enrolment Requirements
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comprising one or more of: a bachelor’s honours degree in a relevant discipline (computer science, software engineering), which includes a research thesis or project, with an overall average grade equivalent
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publications in the fields of materials science, materials engineering, chemical engineering, electrochemistry, inorganic chemistry, process engineering environmental science, etc., are encouraged to apply
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, internal student and commence by 1 January 2026 Have a background in material/mechanical/chemical engineering or chemistry or physics or similar field, and First class or second-class division A bachelor
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research methods Desirable: interest in pursuing pathways between industry and academic research Application process To express your interest, please submit an EOI form address to Prof Katie Ellis
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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
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experience and publications in materials science, materials engineering,chemical engineering, electrochemistry, inorganic chemistry, etc., are encouraged to apply. Application process Future student, please
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, 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
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about potential research projects, please contact Prof Toby Pavey . For information on how to apply for this scholarship, please contact hdr@qut.edu.au . What happens next? Applicants will be contacted
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to apply: Seismic wave propagation theory; seismic data acquisition and processing; signal processing, seismic imaging, geophysical inversion, scientific programming, reservoir modelling. Previous research