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) to isolate pure bioactive microbial natural products. Use spectroscopic (NMR, MS, UV-vis and polarimeter) and chemical analysis to elucidate the structures of microbial natural products. Perform genomics
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for association analysis. Collaborate across disciplines to secure competitive research funding and translate findings to end users. Supervise and mentor HDR students, fostering the next generation of public health
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technologies that support decarbonisation and clean energy goals. The successful applicant will contribute to the computational modelling and design of Prussian blue analogues, spin-crossover metal-organic
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closely related field. Experience creating participatory design and analysis methods tailored to specific contexts of technology use. Evidence of technical ability to develop interactive prototypes
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analysis to estimate ecological parameters, and implementing models in Matlab. You will work closely with a diverse team of around 20 field ecologists and modellers, as well as international collaborators
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, you’ll engage in a diverse mix of activities—from hands-on laboratory work, experimental design, and data analysis through to research publications, presentations, and student supervision. You will play a
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collection, analysis, and the preparation of publications in leading academic journals. Analyse longitudinal survey data, using a variety of advanced statistical analysis techniques Collaborate on grant
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will include: Research: Lead at least two cohort studies (one that includes diverse pain presentations and a smaller cohort for more detailed analysis of a single pain condition), seek and manage
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of industry engagement or the ability to effectively communicate to relevant stakeholders High level of personal integrity, transparency, and capability. Experience in the use and analysis of isotopes
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experience with coding in Matlab, Python, or R. Strong track record in computational science, image analysis, or mathematical modelling of complex systems. Evidence of publications in reputed refereed journals