About the role

Your role will be to develop and apply novel computational and statistical tools to predict the stability of ecological communities. This will involve constructing, optimising, and testing Bayesian hierarchical models and machine learning models, with the aim of predicting community composition and coexistence using environmental-, functional-, and phylogenetic information. Applications and model-testing will focus on existing datasets, primarily of forest ecosystems, but will also include plant, aquatic, and microbial communities as needed.

This role is an open-ended role with funding for up to three years. Start date is negotiable, but ideally in Q1 of .

Appointment at Grade 7 is dependent upon having been awarded a PhD; if this is not the case, initial appointment will be at Grade 6B with payment at Grade 7 being backdated to the date of final submission of the PhD Thesis.

This appointment is subject to UCL Terms and Conditions of Service for Research and Professional Services Staff. Please visit for more information.

Interviews will take place in early .

A job description and person specification can be accessed at the bottom of this page.

If you have any queries about the role, please contact Dr Daniel Maynard, .
If you need reasonable adjustments or a more accessible format to apply for this job online or have any queries about the application process, please contact the HR Administrator.

About you

The successful candidate must hold or be submitting a PhD in a relevant area, including an ecological or environmental discipline, statistics, computer science, data science, or related field. You must have strong computational skills and significant experience working on complex statistical models, ideally using Bayesian or machine-learning approaches. Strong programming knowledge in at least one language are required, ideally in R, Python, or Julia.

Experience using Git, the Stan language, parallel and distributed computing, and/or shell scripting are strongly encouraged but not required. Some knowledge of plant ecology, forest ecology, and/or theoretical ecology is useful but likewise not required.

Experience with the peer-review process is mandatory, as is the ability to prepare initial and final drafts of manuscripts for publication. Excellent written and verbal communication skills are essential, including the ability to keep meticulous records and well-annotated computer code.

What we offer

The UCL Ways of Working supports colleagues to be successful and happy at UCL through sharing expectations around how we work – please see to find out more.

As well as the exciting opportunities this role presents, we also offer some great benefits some of which are below:
• 41 Days holiday (27 days annual leave 8 bank holiday and 6 closure days)
• Additional 5 days’ annual leave purchase scheme
• Defined benefit career average revalued earnings pension scheme (CARE)
• Cycle to work scheme and season ticket loan
• Immigration loan and expenses
• Relocation scheme for certain posts
• On-Site nursery
• On-site gym
• Enhanced maternity, paternity and adoption pay
• Employee assistance programme: Staff Support Service
• Discounted medical insurance