290 phd-studenship-in-computer-vision-and-machine-learning Fellowship research jobs in Australia
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the application of AI and machine learning to identify novel therapeutic targets and advance precision medicine approaches. For further information, please click here to view the full appointment
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methods for monopiles and validating models through centrifuge testing. Contribute to research dissemination through publications, conferences, and supervision of students. About you PhD or equivalent
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opportunities to develop their abilities and advance their careers and our PhD program has launched a thousand research careers. About the opportunity Small-scale fisheries account for 40% of global fish catch
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-quality research publications in econometrics or related fields. You will possess the ability to solve complex statistical problems, show advanced computer literacy with proficiency in relevant software
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team and ensure all key research outcomes and milestones are achieved in alignment with project timelines. Qualifications, skills and experience required A PhD qualification or equivalent in Geology
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and community partners, secure research funding, and contribute to JCU’s broader academic mission. About You Essential: PhD (completed or near completion) in psychology or a related discipline (e.g
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are desirable. To be successful in this position, you’ll have: A PhD degree in Computer Science related field is desirable Industry Experience: Demonstrated industry experience in managing, building, and testing
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hearing care. This role supports a high-impact research program focused on addressing the unmet needs of adults with hearing loss through data-driven policy, service innovation, and community-based
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AUSTRALIAN NATIONAL UNIVERSITY (ANU) | Canberra, Australian Capital Territory | Australia | 29 days ago
delivering project-based learning and actively participate in the broader intellectual and academic life of the School, College and University. Located within the School of Art and Design, the Design program
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-atomic potentials using a combination of classical and machine-learning (ML) approaches (and a new hybrid method recently developed in our group). Some of the types of simulations that will be performed