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of the project in top tier conferences and journals Key Competencies and Requirements: PhD in Electrical and Electronic Engineering/Computer Engineering/Computer Science or related engineering degree At least 1
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with verifiable experience in longitudinal data analyses methods, structural equation modelling, network analysis, machine learning and/or adaptive trial design. Essential are outstanding academic
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Research Fellow position in the mechanistic modelling of pharmaceutical tablet disintegration. This UKRI/EPSRC-funded project offers a unique opportunity to join a dynamic research team collaborating with a
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to PhD students where appropriate to the discipline Contribute to developing new models, techniques and methods Undertake management/administration arising from research Contribute to Departmental/School
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level B and C minimum 3 years post-PhD experience for Level C significant experience conducting original research and engaging in scholarly activity strong analytical skills in modelling time trends and
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neurobiology, systems biology, or neurodegenerative disease models. Prior experience with transcriptomic or molecular analyses in cell culture or animal model systems. Contact Information: Genetics Hire Team
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record in any one of the mentioned fields will be considered very seriously for these positions. Requirements The candidate must have a PhD degree in mathematics or theoretical physics. The candidate must
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chain, particularly how data is captured to develop and operate AI models and the rewards given to data providers. PRIMARY RESPONSIBILITIES The key responsibilities of the position will be to: Lead the
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engineering, computational biology, protein chemistry, data science, or related field. You will bring expertise in biological product purification, along with strong data handling and modelling skills. You will
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demonstrating values-based leadership that supports wellbeing, inclusion, and organisational excellence. This is a research focused position. Further information can be found by viewing UQ’s Criteria for Academic