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analysis to characterise the corona composition and will also quantify the biological stability over time. The candidate will also develop methods to isolate the NP-corona complexes without creating
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with the Principal Investigator Professor Cormac Sreenan and the gVID project Technical Lead. A suitable candidate will have a PhD, 8 years of research/industrial experience and a keen interest in
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(in vitro and/or in vivo). • Proficiency in relevant software for data analysis and structural visualization. • Experience with in-silico discovery of antimicrobial
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through other channels. Person Specification: PhD in a discipline with a quantitative background, including statistics, data science, health science, epidemiology or a related areas. Experience in data
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, Mathematical Modelling and Self-Learning Systems, and Data Science and Analytics as well as a strong PhD programme. The Mathematics Group comprises nine permanent members of staff working across the areas
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anti-microbial resistant bacteria. This will involve evaluating all synthesised candidates through spectroscopic measurements as well as through a range of traditional chemical biology methods
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silico work, including sequence design, data analysis, experimental planning, and writing publications. The postdoc will work closely with the PI and a PhD student. An ideal candidate must hold, or be
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. Optimise nanosheet properties including aspect ratio, defect density, and yield. Prepare and deposit 2DM inks using appropriate printing methods (e.g. liquid-liquid interfacial deposition, inkjet, aerosol
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. To engage in the wider research activities of the Research Group, School or College. To interact closely with postgraduate research students who are studying for a Masters or a PhD and have an agreed role in
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closely with the PI and a PhD student. An ideal candidate must hold, or be on the verge of holding, a PhD in a relevant field, such as DNA nanotechnology, computer science, bioengineering, synthetic biology