World-Leading Doctoral Scholarship in Biology and Statistics2022 entry
The University of St Andrews is pleased to offer a full scholarship funded by St Leonard’s Postgraduate College, to support an exceptional student undertaking doctoral research in the following project:
Developing Novel Methods for Estimating the Abundance of Breeding Grey Seals
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Interdisciplinary approaches, such as statistical ecology, are increasingly needed to tackle pressing environmental challenges. Uniting the disciplines of biology and statistics can help us to better understand and ultimately conserve the environment. For example, monitoring the abundance of animal populations over time is important for effective conservation and management, including sustainable resource acquisition from the environment. However, estimating abundance is difficult for many species that are not always observable (e.g., when at sea or migrating). This is an area of active research and development within the field of statistical ecology.
The grey seal population in the UK presents an ideal opportunity for the development of statistical methods for abundance estimation using a comprehensive long-term data set. This PhD project will lead to innovations in statistical ecology and make real-world contributions to the management of grey seals in the UK.
The UK hosts approximately 40% of the global population of grey seals and the population is protected under both national and international legislation. The Sea Mammal Research Unit (SMRU) at the University of St Andrews has monitored the UK grey seal population for over 30 years. Their findings feed into the NERC Special Committee on Seals (SCOS) reports which are used by UK and devolved governments to inform sustainable management of seal populations and marine spatial planning. However, accurate estimates of population size and trends (e.g., Thomas et al. 2019) depend on reliable estimates of grey seal pup production (i.e., the number of pups born each year). Multiple counts of breeding colonies are conducted over a season, and are combined with information on life history parameters to derive a birth curve and estimate pup production (Russell et al. 2019). With modern statistical methods and computational capabilities, the student, with support from their supervisors, will develop a new pup production model that can account for recent changes in survey methods and sources of observational uncertainty, and ultimately provide more robust estimates of pup production.
The project will be tailored to suit the student’s specific skills and interests, within the overall research topic. We envision that the student will build on a preliminary pup production model developed by the supervisory team to: 1) explore Bayesian approaches to model fitting that incorporate different sources of information (e.g., data, information from previous studies, expert opinion) to improve inference; 2) create a hierarchical multi-year, multi-colony models so that available information from data-rich colonies and years is effectively shared with data-poor colonies and years; 3) develop statistical methods for estimating uncertainty at a sub-population (e.g., management area, regional units) level; and 4) conduct sensitivity analyses via simulation to determine the timing and number of surveys that would maximize the robustness of pup production estimates given available resources. Statistical modelling will be conducted in the statistical software R with model development through packages such as TMB, nimble, and RStan.
References and relevant literature
Jacobson, EK, Boyd, C, McGuire, TL, Shelden, KEW, Himes Boor, GK & Punt, AE. (2020). Assessing cetacean populations using integrated population models: an example with Cook Inlet beluga whales. Ecol App, 30(5), e02114.
Russell DJF, Morris CD, Duck CD, Thompson D, Hiby L. (2019) Monitoring long‐term changes in UK grey seal pup production. Aquatic Conserv: Mar Freshw Ecosyst. 29: 24-39.
Thomas L, Russell DJF, Duck CD, et al. (2019) Modelling the population size and dynamics of the British grey seal. Aquatic Conserv: Mar Freshw Ecosyst. 29:6-23.
Training and Academic Environment
The student will be co-supervised by Dr Debbie Russell, Professor Len Thomas, and Dr Eiren Jacobson, and may choose to matriculate in either Biology or Statistics. The student will develop highly sought-after skills in ecological statistics, specifically advanced modelling techniques that are transferable to a wide variety of topics. The supervisory team have extensive expertise in ecological statistics and its component fields of ecology and statistics. As well as joining lab groups and working with the SMRU Aerial Survey Team, the student will benefit from being part of a wider community of ecologists and statisticians within in the Centre for Research into Ecological and Environmental Modelling (CREEM) and Sea Mammal Research Unit. CREEM is a world-leading interdisciplinary research group at the intersection of statistics, ecology and computing, and CREEM researchers have a strong track record in areas closely related to the PhD topic. The student will have the opportunity to participate in training schemes such as the Academy for Postgraduate Training in Statistics. There will also be additional support available for the attendance of conferences and other professional development activities.
Prior to submitting an application, prospective applicants are welcome to contact the supervisory team to discuss the project and to seek guidance or clarification on preparing application materials. Any pre-application conversations will not form part of the assessment of candidates and will not affect decision making. Enquiries may be addressed to Dr Debbie Russell (dr60@st-andrews.ac.uk), Professor Len Thomas (len.thomas@st-andrews.ac.uk), or Dr Eiren Jacobson (eiren.jacobson@st-andrews.ac.uk).
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Geographical criteria
No restrictions.
Domicile for fee status
No restrictions.
Level of study
Postgraduate Research (Doctoral)
Year of entry
The 2022-2023 academic year at any of the below entry dates:
- August 2022
- September 2022
- October 2022
- January 2023
Schools
- Biology
- Mathematics and Statistics
School selection criteria
Applicants must not already (i) hold a doctoral degree; or (ii) be matriculated for a doctoral degree at the University of St Andrews or another institution.
The supervisory team is committed to a transparent and equitable selection process. We plan to use the following rubric when evaluating applicants and will schedule interviews with the top candidates. Applicants should clearly explain how they meet or exceed these criteria in their personal statement. We will consider the accomplishments of prospective students in the context of their background and experiences. There are no mandatory criteria; applicants may advance to interview even if they do not meet some criteria.
Criteria Does not meet criteria Meets criteria Exceeds criteria Academic Preparation Academic record does not indicate a first or upper second-class degree (or equivalent) in statistics, biology, or a related discipline (0); no MSc in relevant discipline (0) Academic record indicates an upper second-class degree (or equivalent) in statistics, biology, or a related discipline (1); MSc in relevant discipline (1) Academic record indicates a first-class degree (or equivalent) in statistics, biology, or a related discipline (2); MSc with distinction (or equivalent) in relevant discipline (2) Research Engagement and Potential No additional evidence of engagement or attempted engagement with research is included in the application (0) Some evidence of research engagement and potential is provided, e.g., independent research projects or other previous research experience (1) Strong evidence of research engagement and potential is provided, e.g., previous employment as a researcher or published paper(s) (2) Quantitative Skills No university-level training in statistics (0); no experience in computing languages (0) Basic university-level training in statistics (1); some experience in R or another computing language (1) Strong university-level training in statistics (2); considerable experience in R or another computing language (2) Alignment with Research Topic No demonstrated interest in statistical ecology (0) Demonstrated interest in statistical ecology (0.5) Demonstrated interest and/or background in statistical ecology (1) Personal and Professional Preparedness No specific personal development or career goals are articulated (0) Goals are vague, short-term and/or not aligned with program training (0.5) Clearly articulates long-term personal and/or professional goals which align with program training (1) Community Contributions No engagement with public outreach or community building activities (0) Participation in public outreach and/or community building activities (0.5) Leadership roles in public outreach and/or community building activities (1) Additional Considerations
We welcome all applications and will assist the selected student in finding community and support so that they can thrive at St Andrews. In the event that two or more applicants score similarly using the criteria above, we may give preference to applicants who self-identify as Black, Asian, or Minority Ethnic (BAME) because BAME students have been historically underrepresented in statistics and biology PhD programs at St Andrews. Applicants who wish to receive this “tiebreaker” consideration should self-identify in their personal statement.
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Duration of award
Up to 3.5 years. The successful candidate will be expected to have completed the doctorate degree by the end of the award term. The award term excludes the continuation period and any extension periods.
Value of award
The award covers full tuition fees for the award term as well as an annual maintenance payable at the standard UK Research Council rate (the 2021-22 annual rate is £15,609).
Tuition or maintenance award
Tuition and maintenance.
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Doctoral Research at St Andrews
As a doctoral student at the University of St Andrews you will be part of a growing, vibrant, and intellectually stimulating postgraduate community. St Andrews is one of the leading research-intensive universities in the world and offers a postgraduate experience of remarkable richness.
St Leonard’s Postgraduate College is at the heart of the postgraduate community of St Andrews. The College supports all postgraduates and aims to provide opportunities for postgraduates to come together, socially and intellectually, and make new connections.
St Leonard’s Postgraduate College works closely with the Postgraduate Society which is one of the most active societies within the Students’ Association. All doctoral students are automatically welcomed into the Postgraduate Society when they join the University.
In addition to the research training that doctoral students complete in their home School, doctoral students at St Andrews have access to GRADskills – a free, comprehensive training programme to support their academic, professional, and personal development.
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- Apply for admission as a doctoral student. Please see the advice on Research programmes. After applying for your chosen course, you must allow at least four working days for processing and issue of your log in details before you can apply for the scholarship (Step 2).
- Apply separately for the scholarship by logging into My Application.
- Enter the catalogue by following the link in the email, then choosing Scholarships and funding (under 'Useful links') and then clicking View the scholarships and funding catalogue.
- Select 2022/3 as the Academic Year and click Refresh list.
- Locate World-Leading St Andrews Doctoral Scholarships in the list of scholarships (using the filter box if necessary), click Apply and complete the application form.
- You can also use the catalogue to search and apply for other scholarships for which you are eligible.
If you are a current student at St Andrews, you can access Scholarships and Funding through MySaint. However, you should wait until after you have applied for your intended postgraduate programme before doing so, to ensure that the scholarship application is linked to that course.
As part of the scholarship application you will be required to upload a personal statement. This should serve as a cover letter for the research project application as a whole, and should include:
- An outline of your suitability for the project (project criteria can be found in the "Eligibility" and "Project Description" sections above).
- Why the project interests you.
- What you would bring to the project in terms of previous skills and expertise.
- Any ideas that you may have for the realisation of the project.
Please contact pgscholarships@st-andrews.ac.uk with any enquiries about the scholarship application process.
When do applications open?
December 2021
Scholarship application deadline
7 February 2022
When should I apply for the scholarship?
Apply for the scholarship as soon as possible after you have applied for admission.
When will I hear if my application has been successful?
Within two months of the application deadline.