58 linked-data-"https:" "https:" "https:" "Stanford University" Postdoctoral research jobs in Australia
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mindset. Desirable: Experience working with industry partners or on industry-focused research. Knowledge of advanced characterisation techniques (SEM, EDX, XRD, tribology). Experience with data-driven
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the Centre for IoT and Telecommunications (CIoTT) in the School of Electrical and Computer Engineering. CIoTT is internationally recognised for excellence in wireless communications and signal processing and
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density) influence energy dissipation develop mathematical models to predict and explain these effects collect and analyse data, including with the use of machine learning use this knowledge to design
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across large cohorts (e.g., >300 samples) demonstrated experience in data analysis, visualisation, and machine learning, using programming languages such as R or Python excellent interpersonal, verbal, and
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, Professor Feike Dijkstra and Professor Stephen Cattle. The successful applicant will also work closely with CSIRO scientists; including project lead Dr Mark Farrell and Dr Uta Stockmann. For more information
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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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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