Prof Simon Rundle (University of Plymouth)
Dr Oliver Tills (University of Plymouth)
Dr Michal Mackiewicz (University of East Anglia)
Prof John Spicer (University of Plymouth)
This PhD will apply a new, cutting-edge technology, EmbryoPhenomics, to develop novel tools for predicting environmental sensitivity in marine invertebrates. The accurate prediction of how organisms will respond to global change represents a significant scientific challenge but is essential for developing policy decisions and mitigation strategies. Phenomics is a new, technology-enabled approach that uses the high-throughput acquisition of high-dimensional data of the observable phenotype (i.e. morphology, physiology and behaviour) to measure biological responses more robustly and provide a more holistic understanding of the mechanisms underpinning sensitivity. EmbryoPhenomics uses bio-imaging and advanced image analysis to measure the sensitivity of early developmental stages in aquatic species with different life history strategies and will be used to produce novel, sub-lethal phenomic end points that can be used as predictive tools.
The student will work within the new EmbryoPhenomics facility at the University of Plymouth. They will design and carry out experiments assessing the response of marine invertebrates (molluscs and crustaceans; encapsulated and planktonic developers) to current and predicted levels of environmental stressors (temperature, salinity and oxygen) in isolation and in combination; there will also be the opportunity to compare responses under static and fluctuating conditions. They will apply this unique capability for high-throughput phenomics in embryos and identify lethal and sub-lethal responses, including traits and ‘proxy traits’ that are key ‘end points’ of environmental stress.
The student will benefit from a truly, interdisciplinary training in practical and computational Biology, all within an environmental context. As well as learning how to use the EmbryoPhenomics platform, i.e. bio-imaging and data acquisition, image analysis and interpretation, they will receive training in computational Biology (Python, advanced R) and handling large data sets, developmental ecophysiology, and the use of large-scale experiments for addressing questions in environmental biology.
Candidates should have a minimum 2:1 Bachelor degree (or equivalent) in a Biological Sciences subject, or Environmental Sciences with some element of biology. They should also have a good level of numeracy and be willing to learn the computational skills associated with this PhD.