59 data "https:" "https:" "https:" "https:" "Dr" "UCL" Postdoctoral research jobs in Australia
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Macquarie University in Sydney, Australia. You will be working with A/Prof Benjamin Pope and A/Prof Christian Schwab on a full-time, fixed term period for 3 years. This role will develop and apply new data
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analyse data in the manufacturing process. The project is a partnership between Rux Energy and USYD and is a multi-disciplinary effort between scientists and engineers. We are looking for a Postdoctoral
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milestones and deadlines good analytical skills and attention to detail and ability to utilise data analytics and modelling software accordingly experience in space solar cells qualification, acceptance
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large-scale cross-cultural and longitudinal studies in collaboration with international research teams manage multi-site data collection, including ethical approvals and cross-country protocols conduct
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loading Flexible working Additional 3 days of leave over the Christmas Period Access to lifelong learning and career development Progressive HR practices More information on the great staff benefits
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discovery, generating mechanistic data that directly informs the development of next‑generation medicines for neurological disorders Base Salary, Academic Level A $113,400 - $121,054 + 17% superannuation
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essential PhD experience in single-cell research and data analytics, ideally in proteomics or transcriptomics. The candidate should have evidence for high-impact publications, experience working with HPC
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discovery, generating mechanistic data that directly informs the development of next‑generation medicines for neurological disorders Base Salary, Academic Level A $113,400 - $121,054 + 17% superannuation
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and aerosol characterisation, including: -Laser diffraction -Next Generation Impactor (NGI) -Liquid chromatography-based analyses Analyse and interpret experimental data to inform iterative formulation
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likelihood estimators, as well as experience in estimating labour supply models and models of wage dynamics. Ability to work with large datasets, particularly panel and cross section data sets of the types