Senior Statistician Specialising in Environment, Food and Agriculture

Biomathematics and Statistics Scotland (BioSS) is looking for a quantitative scientist who is ready to develop a personal research profile while leading statistical consultancy across the environmental, food and agricultural sciences. Our society is facing multiple challenges, where we need to simultaneously increase food security, reduce our impact on climate change, and increase biodiversity, and the quantitative sciences are key to making better informed responses to these issues. With rapidly evolving technologies generating large and complex data sets, this position will provide exciting opportunities for a committed and innovative scientist to build a stimulating career in a dynamic and collegial working environment. The post offers opportunities to work across a broad range of scientific areas, collaborating primarily with SRUC (Scotland’s Rural College).

The post will provide excellent long-term career opportunities for a suitably qualified statistician or quantitative scientist, offering a stimulating mix of work including collaboration with scientists at leading UK research institutions; interactions with other quantitative experts within and beyond BioSS; a generous time allocation within which to develop an area of quantitative methodological research; the opportunity to advance your career in a supportive environment at BioSS as we continue to grow as a widely-admired centre of quantitative applied research and consultancy.

BioSS is eligible to apply for UKRI funding, and we will be keen for the successful applicant to contribute to, develop and lead proposals as we seek to grow our portfolio of projects. This position will be based at the BioSS unit in Edinburgh.

BioSS is a member of the SEFARI (Scottish Environment, Food and Agriculture Research Institutes) collective (https://sefari.scot/); we have an international reputation for research, consultancy and training in statistics, mathematical modelling and bioinformatics. BioSS offers a stimulating working environment, with over 50 staff and students at four locations, collaborating on applications in plant & crop science, animal health & welfare, environmental science & ecology, and human health & nutrition.

For more information about BioSS please see Home Page ¦ Biomathematics and Statistics Scotland.

Potential applicants are welcome to contact Dr Sarah Brocklehurst () to discuss this position.

Benefits offered

• 35 hour working week as standard.
• Generous entitlement of up to 40.5 days annual leave per year.
• Pension: Employer Contribution of 15% of salary into a Personal Pension Plan, with employee contribution flexibility.
• Self-managed hours and Flexible Working: options to structure your working time, in line with organisational needs, to define a healthy work life balance.
• Employee Assistance Programme: A confidential service available to support employees and their families with work or personal problems.

Main Purpose of Job

• Deliver collaborative research and statistical consultancy across application areas in the environmental, food and agricultural sciences, with particular focus on the needs of SRUC (Scotland’s Rural College).
• Develop a portfolio of personal research in applied statistics, statistical genetics or mathematical modelling motivated by quantitative problems encountered in collaborative environmental, food and agricultural projects.
• Generate additional income by leading, and participating in, applications for funding, and contributing to resulting projects.

Given the seniority of the post, candidates are expected to evidence a track record of achievement; they will be expected to evidence independent initiative and leadership experience.

Main duties of post holder

• Contribute quantitative expertise to collaborative research projects, focussing on several of these areas: soils and crops, animal health, welfare and behaviour, crop and livestock disease control, agricultural emissions, biodiversity, agri-food systems, and agri-economics and social sciences.
• Deliver research, developing statistical, statistical genetics, or modelling methods, with clear relevance to the Scottish Government funded Strategic Research Programme.
• Contribute to the development and delivery of BioSS training courses for research scientists.
• Develop strong collaborative links with specific groups of scientists in the SEFARI and more widely.
• Identify, lead and collaborate in applications for funding, including calls from UKRI, and contribute to management and delivery of resulting projects as appropriate.
• Contribute to meetings with stakeholders from scientific and non-scientific backgrounds.
• Support building new collaborative links with government agencies, NGOs, universities, research institutes and commercial organisations.
• Contribute to raising BioSS’ external profile by presenting work at relevant national and international conferences.
• Take personal responsibility for building, managing and maintaining relationships with specific groups of scientists, external organisations and stakeholders; establish new links and new areas of collaboration; and in all such activities explicitly seek to generate benefit across all of BioSS by acting in support of other staff.

Qualifications/Skills/Knowledge

We will be looking for the following ‘Essential’ and ‘Desirable’ attributes in candidates:

Essential

• A PhD in statistics, biomathematics or another very closely related quantitative discipline, or an MSc with commensurate post-qualification development and work experience.
• Experience of development and use of modern quantitative methods applied to real-world examples. No specific area of experience is ‘essential’, but examples of desirable fields are listed below.A strong track record of research and/or collaboration evidenced by scientific journal and conference papers in a methodological field relevant to the environment, food or agriculture sciences.
• Evidence of collaborative working at the interface between mathematical and other sciences, preferably in a methodological field relevant to the remit of this post.
• Strong general statistical skills, including an understanding of relevant areas such as: experimental design, survey design, regression, mixed models, generalised linear models, generalised additive models, multivariate analysis.
• Good statistical programming ability in R or another high-level statistical programming platform.
• Enthusiasm for development and application of quantitative methods, for collaborating with applied scientists in a range of scientific areas.
• The ability to work independently.
• Evidence of good written communication skills.
• Strong verbal communication skills, including the ability to give effective spoken presentations, to both quantitative and wider scientific audiences.
• Enthusiasm for developing, contributing to, and leading funding applications.
• Evidence of ability to initiate and manage collaborations, lead projects and to manage people.

Desirable

• Different skills sets would fit the remit of the post, any of which would be desirable. For example, experience in any of:Experimental design;
• Advanced multivariate methods;
• Bayesian statistical modelling;
• Statistical methods for socioeconomic research;
• Latent variable models and/or mixture models;
• Development of Bayesian Belief Network or Chain Graph models;
• Individual (agent)-based modelling;
• Statistical genomics.

Experience in statistical methods for socio-economics problems, or in graphical modelling will be particularly welcome. This list is explicitly not exhaustive; all applicants who believe that they have expertise relevant to the post will be welcome.

• Experience in environmental, food and agricultural sciences applications, or closely related fields.
• Experience of communicating with government and commercial clients.
• Experience communicating scientific activity to the public, including use of social media.
• Experience of developing and leading funding applications.

Other Notes

This is a permanent appointment.

We encourage applications from underrepresented groups in STEM, particularly women, BAME and LGBTQ+.

BioSS is an accredited Investors in People Gold Organisation.

BioSS is formally part of The James Hutton Institute.

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