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Job no:516615 Work type:Fixed term - Part-time Campus:Adelaide Categories:Level A, Level B (Level A/B) $78,544 to $131,335 per annum plus an employer contribution of 17% superannuation applies
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(Level A) $78,544 to $105,611 per annum plus an employer contribution of 17% superannuation applies. Fixed-term, part-time position (0.6 FTE) available for 2 years. Grant Funded Early Career
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drainage during droughts, and coastal floodplain development often trigger geochemical reactions that generate highly acidic waters enriched in dissolved aluminium. Elevated aluminium concentrations pose a
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interest Expressions of interest should be submitted to Prof David Lewis and and A/Prof Phil van Eyk (david.lewis@adelaide.edu.au and philip.vaneyk@adelaide.edu.au ) and the position will be open until
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significant agricultural problem, while gaining expertise in advanced soil science techniques and working within a multidisciplinary team of researchers. Students with relevant expertise and interest in soil
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machine learning frameworks like PyTorch. The candidate should demonstrate strong analytical abilities, an eagerness to learn and solve complex problems, and possess effective collaboration skills
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aspects of our work, with a particular focus on sustainable energy solutions and integrating data-driven decision-making tools into business operations. This position is designed for individuals who
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1/10/2025 with the name of scholarship in the subject heading. Applications will be assessed as and when received and the PhD position may be filled ahead of this date if the suitable candidate is
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parameters will be assessed. The goal of the projects will be to identify best clinical practice for this complex surgical problem. The projects will be separated along clinical and radiological/engineering
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conference and review meetings. Interpersonal skills to work as an independent researcher and as a member of a diverse research team, collaborating toward goals, solving problems, and developing scientific