Research Assistant, Wellcome Ecology/Data Science

Natural History Museum; City of Westminster; On-site; GBP 60,000 - 80,000; Full time

Job summary

A renowned cultural institution in Westminster seeks an individual with a Master’s degree to analyze biodiversity data related to climate impacts. Responsibilities include developing statistical methods, managing data workflows, and contributing to research publications. The ideal candidate will have a solid background in statistical analysis and experience in coding with R or Python. Competitive benefits include generous holiday allowances, pension contributions, and various training opportunities.

Benefits

27.5 days holiday plus 8 bank holidays

Defined contribution pension scheme

Season ticket loan

Life insurance

Free admission to exhibitions

Staff discount at Museum shops

Training initiatives

Qualifications

• Master's degree (or equivalent experience) is required.
• Strong statistical and computational analysis background sought.
• Experience with AI methods is beneficial.

Responsibilities

• Utilize biodiversity databases to analyze ecological processes.
• Develop methods for habitat-use preferences from datasets.
• Provide expertise in coding workflows and support lab research.
• Publish research and explore new research directions.

Skills

Statistical analysis

Computational analysis

Coding in R or Python

Machine learning

Data management

Use of large language models

Version control

Education

Master’s degree in a relevant quantitative discipline

Job description

Overview

Understanding and communicating how climate and land‑use change affect human societies is essential for driving lasting shifts in our collective behaviour. This post will be based in a lab that studies the impacts of global change processes, such as climate, land‑use and demographic change, on biodiversity and human health.

Responsibilities

• Use large biodiversity databases (e.g., GBIF) to link ecological processes to disease dynamics and develop statistical methods to account for biases in underlying data.
• Develop movement‑pattern inference methods from static observations to determine habitat‑use preferences from large‑scale occurrence datasets.
• Contribute expertise in reproducible coding workflows, data management and machine learning to support the wider lab.
• Help publish ongoing research and pursue new research directions.

Qualifications

• Master’s degree (or equivalent experience) in a relevant quantitative discipline.
• Strong background in statistical and computational analysis; confident using coding environments such as R or Python.
• Experience with AI methods, large‑language models, open data, version control and data management will be very useful.
• Ability to work independently, manage time effectively and contribute productively within a multidisciplinary research team.

Benefits

• 27.5 days holiday plus 8 bank holidays (full time equivalent)
• Generous defined contribution Natural History Museum Pension Scheme (employer contribution 4 - 10%)
• Season ticket, bicycle and rental loan
• Life insurance
• Free admission to our exhibitions and many other paid exhibitions at museums, galleries and institutions across London and the UK.
• Staff discount at our Museum shops and cafes
• Wide variety of training initiatives and opportunities to build skills.