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modern Bayesian modelling frameworks such as Stan, Turing.jl, and PyMC, including automatic differentiation frameworks, MCMC sampling algorithms, and iterative Bayesian modelling. Special attention will be
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our software development team, developing novel scientific algorithms and applications in the areas of spectroscopic analysis and mining of the science data catalogues extracted from the pipelines
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bioprocessing technologies to deliver efficient pathways for upcycling captured carbon into high value products. The successful candidate will have a PhD, or be studying towards a PhD, in synthetic biology or a
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obtaining) a PhD in Engineering or other relevant area Knowledge and experience in: Material flow analysis, environmental assessment, emissions accounting or other topics and tools of Industrial Ecology
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A PhD is desirable but not required. Other industry, city government or research experience that demonstrates the capability to produce independent original research is also desirable. Very good
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suited to candidates with strong quantitative and analytical skills and a PhD (or near completion) in cancer epidemiology or a related field. Applicants should have experience in applying or developing
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must either have a PhD in a relevant biological subject or have submitted or about to submit their PhD thesis. Candidates must also have demonstrable expertise in biochemistry, cell biology and/or
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and experience required to perform the role are an aerothermal PhD with a combination of experimental, numerical and low order modelling experience. The PhD must be completed or near completion, and
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on the genetics of appetite and obesity. Candidates should be of postdoctoral level with relevant experience of canine or/and human genomics, or molecular biology. Candidates without PhD but significant expertise
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at conferences and seminars. The successful applicants may also be required to assist in the supervision of student projects in the lab. Applicants must have or be close to obtaining a PhD in Plant Biology