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Field
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collaborating with colleagues to address more complex challenges. You will play an active role in strengthening research capability within the School, supporting students informally, engaging with academic and
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processes, particularly in complex or technically challenging settings. To address these questions, the lab develops and applies new methods for metabolomics, lipidomics, and ¹³C metabolic flux analysis, as
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the ability to perform complex data analyses. Has experience with implementing computer-based experiments as well as field experiments. Has professional proficiency in English, both written and spoken
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engineering using genetic modification can solve some of these problems, but introduces regulatory complexities and biological challenges of it’s own. Epigenetic editing, the controlled reprogramming
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larger network of PIs and postdocs and technicians based at the Universities of Manchester and Liverpool. The post will include developing and optimizing molecular biology protocols for high-throughput
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network excitability following traumatic brain injury using a variety of techniques, including in vivo whole-cell recording and two-photon microscopy, brain slice physiology, and genetic manipulation
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societies govern complex human, animal and environmental health challenges? Do you enjoy working across disciplines, engaging with diverse partners, and translating research into actionable strategies
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, agrochemicals, and food industries. There are multiple opportunities to collaborate, take part in network events and undertake research placements within this project. You will have a PhD in Physical Sciences
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University of New Hampshire – Main Campus | New Boston, New Hampshire | United States | about 2 months ago
complexes, networks and regulators implicated in diseases using a combined approach of biochemistry, proteomics and cell biology, while being a contributor to advancing research projects supported by NIH and
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Professor Evan Myers, Core Faculty Member of the Margolis Institute; this second project is funded from NIH/NCI Cancer Intervention and Surveillance Modeling Network (CISNET) comparative modeling funding and