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"Research Associate (Fixed Term)"

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Research Associate (Fixed Term)

Research Associate

2026-03-08

Location

Cambridge

University of Cambridge

Type

Fixed Term

Salary

£37,694-£46,049

Required Qualifications

PhD in ecology, biology or conservation
Strong field experience in Brazilian forests
Remote sensing and spatial analysis expertise
Species distribution modelling
Proficiency in R/Python
Experience with biodiversity datasets

Research Areas

Biodiversity recovery
Land-use change
Wood production strategies
Cerrado and Atlantic Forest biomes
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Research Associate (Fixed Term)

Research Associate (Fixed Term)

We are seeking a highly motivated Research Associate to support an exciting interdisciplinary research programme focused on biodiversity recovery, land-use change, and wood production strategies across the Cerrado and Atlantic Forest biomes in Brazil. This position will contribute to cutting-edge research linking field biodiversity data, remote sensing, and landscape-scale scenario modelling, with the aim of identifying pathways that balance wood production with biodiversity protection and carbon storage. The candidate will be expected to engage with forestry stakeholders to ensure research can help contribute to improved landscape-scale management practices for biodiversity.

The successful candidate will join an interdisciplinary research environment within the Cambridge Conservation Initiative (CCI) - a unique collaboration between the University of Cambridge and leading global conservation organisations - as part of the Conservation Science Group. The post will also support research aligned with the Suzano programme, a major long-term collaboration that links Cambridge research with applied forestry and restoration challenges in Brazil. The programme provides a rare opportunity to connect field biodiversity monitoring, remote sensing, and scenario modelling with real-world landscape planning and stakeholder decision-making at scale.

Key Responsibilities

  • Collating and harmonising biodiversity datasets tracking vertebrate abundances across the Cerrado and Atlantic Forest.
  • Conducting targeted fieldwork to address key data gaps in under-sampled forest types and land-use systems, including in plantation and secondary forests.
  • Quantifying recovery trajectories and species habitat use across secondary forests and plantations of different ages and management histories.
  • Developing species distribution models through time, connecting species abundance and occurrence records with remotely-derived predictor variables.
  • Assembling and analysing commercial datasets on timber harvesting and the economics of wood production.
  • Evaluating large-scale, spatially explicit landscape strategies for wood production and forest restoration, including scenario pathways that balance biodiversity outcomes with production targets.

Essential Skills and Experience

  • PhD in a relevant subject (e.g., ecology, biology, conservation).
  • Strong field experience conducting biodiversity surveys across diverse forest and land-use systems in Brazil.
  • Strong quantitative and analytical skills, including expertise in:
    • Remote sensing and spatial analysis.
    • Landscape-scale scenario planning considering production and conservation outcomes.
    • Species distribution modelling.
    • Biodiversity modelling using abundance or occurrence data.
  • Experience working with Brazilian environmental, land-use, or biodiversity datasets.
  • A willingness to engage with forestry and land-use stakeholders to develop coherent, realistic scenarios that balance wood production with conservation objectives.
  • Experience working with large biodiversity databases and harmonising multi-source datasets.
  • Proficiency in R and/or Python for ecological modelling and spatial workflows.
  • Familiarity with restoration ecology, forestry, or conservation planning in a Brazilian context.
  • Willingness to spend substantial periods of time in Brazil and in Cambridge.

Fixed-term: The funds for this post are available for 12 months in the first instance, with the possibility of extension subject to the availability of funds.

Applications are welcome from internal candidates who would like to apply for the role on the basis of a secondment from their current role in the University.

Flexible working requests will be considered.

We particularly welcome applications from candidates from a BME background for this vacancy as they are currently under-represented at this level in our Department.

Click the 'Apply' button below to register an account with our recruitment system (if you have not already) and apply online.

For informal enquiries, please contact: Professor Andrew Balmford apb@cam.ac.uk or Dr Gianluca Cerullo grc38@cam.ac.uk

If you have any queries regarding the application process, please contact Paulina Lasocka or Anastasia Nezhentseva hr@zoo.cam.ac.uk

Please quote reference PF48884 on your application and in any correspondence about this vacancy.

The University actively supports equality, diversity and inclusion and encourages applications from all sections of society.

The University has a responsibility to ensure that all employees are eligible to live and work in the UK.

Apply online

Key information

Department/location
Department of Zoology

Salary
£37,694-£46,049

Reference
PF48884

Category
Research

Date published
19 February 2026

Closing date
8 March 2026

Tell them AcademicJobs.com sent you!

Apply Now

Frequently Asked Questions

🎓What are the essential qualifications for this Research Associate role?

Candidates must hold a PhD in ecology, biology, or conservation. Key requirements include strong field experience in biodiversity surveys across Brazilian forest and land-use systems, expertise in remote sensing, spatial analysis, and species distribution modelling, proficiency in R and/or Python, and experience harmonising biodiversity datasets. Familiarity with Brazilian restoration ecology or forestry is essential. Explore research jobs or postdoc success tips for preparation.

🔬What are the key responsibilities of the Research Associate position?

Responsibilities include collating biodiversity datasets from Cerrado and Atlantic Forest, conducting targeted fieldwork in plantations and secondary forests, developing species distribution models, analysing timber economics data, and evaluating landscape-scale strategies balancing wood production with biodiversity and carbon storage. This supports the Cambridge Conservation Initiative and Suzano programme. See related research assistant jobs.

🌳Is fieldwork required, and where will it be conducted?

Yes, the role involves targeted fieldwork to fill data gaps in under-sampled Brazilian forest types, including plantations and secondary forests in Cerrado and Atlantic Forest biomes. Expect substantial periods in Brazil alongside time in Cambridge. Strong prior Brazil field experience is essential. Check postdoc opportunities for similar roles.

📝How do I apply for this fixed-term Research Associate job at University of Cambridge?

Click the 'Apply' button to register and submit online via the recruitment system. Quote reference PF48884. Informal enquiries to Professor Andrew Balmford (apb@cam.ac.uk) or Dr Gianluca Cerullo (grc38@cam.ac.uk). Closing date: 8 March 2026. University supports equality, diversity, and inclusion; BME candidates encouraged. Ensure UK work eligibility. Visit university jobs for more.

💰What is the salary, duration, and any flexibility for this role?

Salary: £37,694-£46,049. Fixed-term for 12 months initially, with possible extension. Flexible working requests considered; internal secondments welcome. Location: Department of Zoology, Cambridge, with Brazil travel. No visa sponsorship mentioned; UK eligibility required. Learn about professor salaries and university salaries for context.

🌍What research environment will the Research Associate join?

Join the Cambridge Conservation Initiative (CCI) and Conservation Science Group, collaborating with global conservation organisations and the Suzano programme on applied forestry in Brazil. Focus on linking field data, remote sensing, and scenario modelling for stakeholder-engaged landscape management. Ideal for those interested in research jobs in conservation.
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