Data science & nanopore-sequencing to uncover hidden biodiversity and ecological interactions

• Supervisors: Yannick Wurm (QMUL), Dr. Chris Laumer (NHM)
• Studentship Funding:
• Name: Joint Studentship
• Funder: Royal Society and QMUL
• Application Deadline: 23:59PM, 19th May 2024
• Expected Start Date: Sept 2024

Download this document for further details, eligibility criteria and how to apply. [PDF 180KB]

Project Overview

Applications are open for a 4-Year funded PhD Studentship at the Natural History Museum and the School of Biological and Behavioural Sciences (SBBS) at Queen Mary University of London.

Working as part of an interdisciplinary team, you will use innovative genomic technologies such as Oxford nanopore sequencing, combinatorial indexing, and develop state-of-the-art bioinformatics, genome analysis, and phylogenetics pipelines. The toolkit you will help build will be transformative, greatly accelerating our ability to catalogue, understand and interrogate these hidden meiofaunal species.

We will apply long-read transcriptome sequencing, robotic automation tools, and single-cell genomics approaches to obtain hundreds of phylogenetically useful gene sequences from thousands of specimens. This enables us phylogenetically place each sample and delimit cryptic species with high confidence. These data also reveal the presence and identity of eukaryotic symbionts and gut contents, which informs our understanding of ecological interactions within meiofaunal communities. Your focus will be to develop automated analysis pipelines and visualisation methods to best make sense of the resulting unprecedented amounts of data we will generate. 

At the Natural History Museum (NHM), we’ve demonstrated the utility of “transcriptome skimming” data in small-scale pilot datasets. We now must discover how to apply it at scale and develop appropriate software tools to allow a broader community of researchers to reap its benefits. At the NHM and Queen Mary University of London (QMUL), you will develop bespoke bioinformatics tools to quality-control, assemble, and mine transcriptome skim data for phylogenetic markers and to iteratively build very large (100,000+ specimen) phylogenies. 

Additional goals include using these data to inform community composition and species interactions, and learning to complement transcriptome-skim datasets with metabarcoding-based methods. If desired, you will also have the opportunity to develop taxonomic expertise in a group of your choice. 

The successful candidate will participate in exciting UK and overseas fieldwork (with 2025 trips planned in Norway, New Caledonia, and beyond) and in globally threatened habitats including temperate rainforests and marine seagrass meadows.

Find out more about the Wurm Lab here.

Find out more about the School of Biological and Behavioural Sciences on our website.

Research Environment

Your time will be split between QMUL and the NHM. 

At QMUL, you will join a dynamic and supportive team of collaborative researchers who enthusiastically enjoy life and doing impactful innovative science (https://wurmlab.com). We work at the interface between the Centre for Biodiversity and Sustainability

, the Centre for Evolutionary and Functional Genomics, and the Digital Environment Research Institute. Some of our track record is outlined at https://wurmlab.com, https://sequenceserver.com, https://sensibee.io and https://pollinator.health.

In the Laumer group at NHM, you will be supported by a dedicated technician, and will benefit from interactions with other PhD and Masters students as well as collaborators and visitors from the Netherlands, Germany, Norway, Denmark, Canada, and beyond. 

This will be a wide-ranging project, providing you with training in molecular biology & genomics, microscopy, fieldwork techniques, bioinformatics, data science, statistics, machine learning, and software development. 

This studentship will also provide opportunities to develop your social scientific abilities, including scientific communication with experts, interdisciplinary colleagues, and laypersons, collaboration with a diverse team, and eventually, supervision and leadership of more junior lab members. 

You will present your work at conferences domestically and internationally, draft high-impact papers and fundable grant proposals, and interact with diverse stakeholders. You will have ample opportunity to steer your thesis research to fit your particular interests and expertise.

Find out more about the School of Biological and Behavioural Sciences on our website.

Entry Requirements & Criteria

We are looking for candidates to have or expecting to receive a first or upper-second class honours degree and a Master’s degree in an area relevant to the project such as evolutionary ecology, systematics, taxonomy, molecular evolution, bioinformatics. Candidates must also have experience conducting research in a laboratory environment, whether dry or wet lab.

Knowledge of phylogenetics, python and R programming, and web development, would be highly advantageous but are not required.

Find out more about our entry requirements here.

Funding

The studentship is funded by the Royal Society and QMUL. It will cover home tuition fees, and provide an annual tax-free maintenance allowance for 4 years at the Royal Society rate as follows: 

• Year 1: £22,410
• Year 2: £23,204
• Year 3: £23,901
• Year 4: £24,618

Please find out more about funding and eligibility via Wurm_Laumer_SBBS NHM Joint Studentship Details_May 2024 [PDF 180KB]

Any further queries can be sent to the sbbs-pgadmissions@qmul.ac.uk 

How to Apply

Formal applications must be submitted through our online form by the stated deadline for consideration.

Find out more about our application process on our SBBS website.

Informal enquiries about the project can be sent to Prof. Yannick Wurm at y.wurm@qmul.ac.uk or Dr. Chris Laumer at christopher.laumer1@nhm.ac.uk

Admissions-related queries can be sent to sbbs-pgadmissions@qmul.ac.uk.

Further details can be downloaded here: Wurm_Laumer_SBBS NHM Joint Studentship Details_May 2024 [PDF 180KB]

Apply Online