Senior Statistician for Food Systems, Human Health and Nutrition

Main Purpose of Job

The person employed in this position will be expected to play a key role in further developing BioSS activities in the Human Health and Nutrition, Food Security and Food Safety application areas. They will develop and apply novel statistical methods for use in these fields. They will be expected to interact with quantitative specialists in BioSS and in the wider statistics and modelling community, and with a wide range of collaborators across the natural sciences; predominantly those working at the Rowett Institute, the Hutton, and the other SEFARI. This person will be expected to:

• Deliver collaborative research and statistical consultancy across these fields, with particular focus on the needs of the Rowett Institute.
• Develop a portfolio of personal research in applied statistics, motivated by quantitative problems relevant to their collaborations.
• 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, demonstrating independent initiative and leadership experience.

Main Duties of Postholder

• Provide local on-site leadership for the Food Systems, Human Health and Nutrition application area, building relationships with Rowett Institute scientists.
• Provide support to the Principal Statistician currently leading BioSS application-led work in this field; if the post holder is successful in the role, the longer-term objective is for them ultimately to lead BioSS’s work in this area.
• Develop and deliver innovative research relevant to systems-oriented science. Various skill sets could be relevant, but experience in the development and use of causal inference methods, Bayesian belief networks, chain event graphs or (in general) probabilistic graphical models would be particularly welcome, given their relevance to work at the Rowett Institute and Hutton Aberdeen.
• Collaborate with SEFARI scientists on research projects with a strong statistical modelling component, contributing to projects in the next RESAS Strategic Research Programme.
• 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.
• Build, manage and maintain 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.
• Contribute to the development and delivery of BioSS training courses for research scientists.

Person Specification - Qualifications/Experience/Skills:

Essential

• A PhD in statistics or another very closely related quantitative discipline, or an MSc with commensurate post-qualification development and work experience. 
• Experience developing and applying modern quantitative methods to real-world statistical data analysis problems.  No specific area of experience is ‘essential’, but examples of desirable fields are listed in the next section.
  • A strong track record of research and/or collaboration evidenced by scientific journal and conference papers in a methodological field relevant to food systems, human health, or nutrition.
  • Evidence of collaborative working at the interface between mathematical and other sciences, preferably in a methodological field relevant to the remit of this post.
  • Experience in applying probabilistic graphical modelling or related statistical methods to real world applications is highly desirable.
• Strong general statistical skills, including an understanding of relevant areas such as experimental design, mixed models, generalised linear models, generalised additive models, multivariate analysis, meta-analysis.
• Good statistical programming ability in R or another high-level statistical programming platform.
• Enthusiasm for the development and application of quantitative methods, and for collaborating with applied scientists across a range of scientific disciplines.
• 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 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:
  • Developing Bayesian Belief Network or Chain Event Graph models;
  • Multivariate analysis of large metabolomic, proteomic or genomic datasets;
  • Causal inference;
  • Meta-analysis.

Experience in probabilistic graphical modelling will be particularly welcome.  This list is explicitly not exhaustive.

• Experience in the human health, nutrition, food security or food safety domains.
• 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.

Benefits offered

• Employee Assistance Programme (EAP) - A confidential service available to support employees and their families with work or personal problems. Providing access to professional counsellors, psychologists, and work-life consultants available to help and support individuals in tackling all types of problems.
• Annual Leave – Generous entitlement up to 40.5 days a year, with carry over possible and guaranteed time-off for Christmas.
• Pension - Employer Contribution of 15% in a Personal Pension Plan and employee contribution flexibility.
• Self-managed hours and Flexible Working – option to manage and spread your working time in line with organisational needs to create a healthy work life balance.