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Field
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About the Role We are looking for a highly motivated and skilled Wet Lab Postdoctoral Research Associate to join our team and contribute to an established and highly successful research program
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experience in a wet biological laboratory with research experience in cell and molecular biology. Preferred Qualifications Education: PhD in subject areas related to cell and molecular biology and
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‑on wet‑lab and in vivo therapeutic discovery in a funded translational program Base Salary, Academic Level A $113,400 - $121,054 + 17% superannuation About the opportunity The School of Life and
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‑on wet‑lab and in vivo therapeutic discovery in a funded translational program Base Salary, Academic Level A $113,400 - $121,054 + 17% superannuation About the opportunity The School of Life and
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project students. The research activities will take place in the state of the art facilities provided by NDCN including access to wet lab space, cell culture and advanced imaging. The Neural Injury Group
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and clinical teams, or (ii) a hybrid profile combining wet-lab expertise (e.g. molecular biology, genomics, epigenetics) with computational skills and an interest in integrating multimodal data
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-based wet lab postdoc for the Experimental Medicine Collaboration (EMC) collaboration working under the supervision of EMCRF Director Prof Chris Buckley and will closely collaborate with other team
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of academia and industry. The post-holder will be the Oxford-based wet lab postdoc for the Experimental Medicine Collaboration (EMC) collaboration working under the supervision of EMCRF Director Prof Chris
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Postdoctoral Research Associate - Hybrid Computational-Experimental Scientist in Bacterial Drug Resp
to antibiotics and host-like conditions. • Develop and apply statistical or machine-learning methods for interpreting single-cell and genomic datasets. • Work closely with wet-lab scientists to design perturbation
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their skills to improve patient outcomes through impactful biomedical research. You will take a lead role in conducting wet lab experimentation, applying state-of-the-art single-cell multiomic approaches