Senior Quantitative Scientist for Environment & Agriculture

Ciwmjobs; City of Edinburgh; Hybrid; GBP 60,000 - 80,000; Full time

Benefits offered by this job

35 hour working week

40.5 days annual leave

Pension: Employer contribution 15%

Flexible working hours

Employee Assistance Programme

Job summary

BioSS in Edinburgh is seeking a quantitative scientist to lead statistical consultancy across environmental, food and agricultural sciences while developing a personal research portfolio.

You will collaborate with SRUC and other UK institutions, applying modern quantitative methods to real-world data. The role offers opportunities to develop funding proposals and to grow as a leader in quantitative applied research.

Qualifications

• PhD in statistics, biomathematics or closely related quantitative discipline.
• MSc with commensurate post-qualification development and experience.
• Strong track record in research or collaboration with scientific outputs.

Responsibilities

• Deliver collaborative research and statistical consultancy across environmental, food and agricultural sciences.
• Develop a personal research portfolio in applied statistics, statistical genetics or mathematical modelling.
• Lead funding applications and contribute to projects from UKRI calls.
• Develop training courses for research scientists and build collaborations with SEFARI groups.
• Establish and manage collaborations with government, NGOs, universities and industries.
• Present work at national and international conferences and raise BioSS profile.

Skills

Statistical programming

Quantitative methods

Strong communication

Independent working

Education

PhD in statistics or biomathematics

MSc with commensurate experience

Tools

R

Python

SAS

Job description

BioSS in Edinburgh is seeking a quantitative scientist to lead statistical consultancy across environmental, food and agricultural sciences while developing a personal research portfolio.

You will collaborate with SRUC and other UK institutions, applying modern quantitative methods to real-world data. The role offers opportunities to develop funding proposals and to grow as a leader in quantitative applied research.