12 parallel-phd Fellowship research jobs at University of New South Wales in Australia
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, and PhD students conducting research focussed on ocean dynamics, connectivity, hydrodynamic model development and observing system design. The team are based in the School of Biological Earth and
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, and a PhD research program with over 120 students. 40 academic staff conduct experimental research in many areas of Psychology, including behavioural and cognitive neuroscience, perception, learning
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://www.unsw.edu.au/engineering/our-schools/photovoltaic-and-renewable-energy-engineering Skills & Experience: A PhD in photovoltaic engineering or related discipline, and/or relevant work experience. Knowledge and
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applicant (Selection Criteria) To be successful in this role you will have: A PhD in Chemistry, Biotechnology, Nanotechnology, or a related discipline. Strong prior experience in DNA nanoscience and/or DNA
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of yourself or others. About the successful applicant (Selection Criteria) To be successful in this role you will have: A PhD in Chemistry, Chemical Engineering or Materials Science. Demonstrated prior research
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who holds the following: A PhD in a biomedical, health, or related discipline, supported by extensive professional experience across academic research, scientific writing, grant development, and
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significant interaction with other scientists and clinical partners. Some skills required: A PhD in reproductive biology, cell biology, developmental biology, molecular biology or a related discipline
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Fellow will have the opportunity to lead statistical analyses of large-scale clinical registry and administrative datasets. Some key skills required: A PhD in health data science, and/or relevant work
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of Australia’s nuclear technology sector. For more information please visit - https://www.unsw.edu.au/research/nuclear-innovation-centre Skills & Experience A PhD in a related discipline, and/or relevant work
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-renewable-energy-engineering Skills & Experience: A PhD in Computer Science or a related field. Thorough theoretical background in machine learning and deep learning. Demonstrated experience in developing