About the Project
This project will use a combination of genomics, phylogenetic inference, and statistical models to better understand the causes and consequences of the evolution of larval development in marine and terrestrial invertebrates. The student will gather and curate data available in databases (e.g., NCBI) and publications to assemble a ‘tree of larval development’, for both marine and terrestrial groups. Mining the data, the candidate will then extract key insights on the potential ways through which larval development evolves, as well as how this allowed for adaptive radiation of marine and terrestrial species in parallel. The candidate will use bioinformatic tools and statistical modelling to extract similarities and differences in genetic and life-history characteristics (e.g., lifespan, reproduction) between species, creating a phylogenetically accurate description of the evolution of larval development across taxa.
This project is primarily designed to be desk-based, where the student will make use of the unprecedented number of datasets available in the public domain, synthesise existing knowledge, create new solutions, and if possible, use modelling to revolutionise our understanding of larval development. The project will be conducted primarily as Distance Learning, allowing the student to undertake the project away from the University of Aberdeen. Students will be in regular contact with their supervisory team by Virtual Conference and encouraged to visit Aberdeen if feasible. The student will be supported by regular meetings with the supervisors and through social events with other graduate students at SBS (e.g. journal club). Within the group, the student will have the opportunity to develop quantitative skills through online/MOOC courses in platforms (e.g., DataCamp), genetic skills through online courses (e.g., Physalia) and writing skills for academic audiences and general public. The student is expected to engage in outreach projects throughout the PhD.
The successful applicant will have a high level of self-discipline to work long-periods of time at home, showing strong commitment to the project and understanding the broad impacts of the project to the wider community. Willingness to learn new skills and make an impact in local communities are essential. Quantitative skills are not mandatory, although the applicant should be passionate about the opportunity of working with data science. Part-time PhD is possible as long as the candidate has a clear understanding of the requirements and workload necessary for completing a successful PhD.
To submit an application please visit View Website
-Apply for 'PhD in Biological Science- Distance Learning'
-State the name of the lead supervisor on your application
-State the name of the project
Please note that we will not proceed with applications that have not stated their intended funding source. Applicants will be expected to have suitable computing materials to enable them to work from home at a distance to undertake this project.
Havenhand, J.N., 1993. Egg to juvenile period, generation time, and the evolution of larval type in marine invertebrates. Marine ecology progress series. Oldendorf, 97(3), pp.247-260.
Emlet, R.B., 1991. Functional constraints on the evolution of larval forms of marine invertebrates: experimental and comparative evidence. American Zoologist, 31(4), pp.707-725.
Wang, J., Zhang, L., Lian, S., Qin, Z., Zhu, X., Dai, X., Huang, Z., Ke, C., Zhou, Z., Wei, J. and Liu, P., 2020. Evolutionary transcriptomics of metazoan biphasic life cycle supports a single intercalation origin of metazoan larvae. Nature Ecology & Evolution, 4(5), pp.725-736.
Haug, J.T., 2020. Why the term “larva” is ambiguous, or what makes a larva?. Acta Zoologica, 101(2), pp.167-188.
Khalturin, K., 2020. The origin of metazoan larvae. Nature Ecology & Evolution, 4(5), pp.674-675.
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