About the Project
About the project
Language barriers can profoundly affect how scientific evidence is produced, synthesised and applied to biodiversity conservation. These barriers are especially important in conservation because many of the world's most biodiverse regions are also highly linguistically diverse and are located in countries where English is not widely spoken.
Our translatE project has developed a framework describing three major pathways through which language barriers can impede evidence-based conservation:
- Generation of evidence: non-native English speakers may face additional time, financial and emotional costs when reading, writing, publishing, presenting and collaborating in English.
- Synthesis of evidence: scientific evidence published in languages other than English may be overlooked in systematic reviews, meta-analyses, global biodiversity assessments and other forms of evidence synthesis.
- Application of evidence: evidence available only in English may not be accessible to conservation practitioners, policymakers and other knowledge users who prefer or require information in other languages.
The rapid development and adoption of artificial intelligence (AI) could substantially reduce all three types of language barriers. AI may help researchers write and communicate in English, enable evidence synthesis across languages, and translate scientific findings into languages used by local decision-makers. There is currently limited empirical evidence showing whether AI has reduced these barriers in practice.
This PhD project will investigate whether, how and for whom AI has changed the three types of language barriers in biodiversity conservation. The successful candidate will develop the project in collaboration with the supervisory team. The candidate will be encouraged to shape the precise questions and methods. Potential questions include:
- Evidence generation: Has access to AI reduced the time, financial and other disadvantages experienced by conservation researchers who use English as an additional language?
- Evidence synthesis: Has AI enabled systematic reviews and global biodiversity assessments to identify and include more evidence published in languages other than English?
- Evidence application: Has AI increased the accessibility and use of scientific evidence among conservation practitioners and policymakers working in languages other than English?
This interdisciplinary project could combine quantitative and qualitative methods, including:
- global surveys of conservation researchers and decision makers;
- interviews or focus groups involving participants from diverse linguistic and geographical backgrounds;
- bibliometric analyses of multilingual publishing and citation patterns; and
- analyses of systematic reviews or biodiversity assessments.
The project will produce evidence that can inform:
- the responsible use of AI in multilingual conservation science;
- methods for incorporating non-English-language evidence into evidence synthesis;
- approaches to communicating conservation evidence in locally relevant languages; and
- broader debates about linguistic diversity, research equity and the future of scientific communication.
Research environment
The candidate will join the translatE project, an international and interdisciplinary research initiative working to understand the consequences of language barriers and develop solutions for a more multilingual, equitable and effective scientific community (see coverage in Nature's Changemakers series). The candidate will also be part of the broader Kaizen Conservation Group.
The project will be based at the School of the Environment, The University of Queensland (UQ) in Brisbane, Australia. The UQ School of the Environment and the Centre for Biodiversity and Conservation Science are a leading centre for biodiversity conservation research, bringing together expertise in ecology, conservation biology, environmental science, social science, and policy. Its interdisciplinary and solution-oriented research is supported by strong partnerships with governments, conservation organisations, industry, and local communities, providing PhD candidates with an excellent environment to conduct research with real-world impact.
UQ is committed to fostering an equitable and inclusive community in which students and staff from diverse cultural, linguistic and personal backgrounds feel welcomed, respected and supported. Brisbane complements this environment as a vibrant and culturally diverse city, offering international students an inclusive and welcoming place to live and study.
Candidate profile
We are looking for a curious, collaborative and highly motivated candidate with an interest in biodiversity conservation, language barriers, research equity and the societal effects of artificial intelligence.
Relevant disciplinary backgrounds for this project may include, but are not limited to:
- ecology or conservation science;
- evidence synthesis;
- information science;
- a related interdisciplinary field.
Experience in one or more of the following would be valuable:
- quantitative data analysis, including Python and R;
- survey, interview or focus-group research;
- systematic reviews or meta-analysis;
- bibliometric or text-based analysis;
- working across languages or cultural contexts;
Applicants do not need to possess all these skills. The project can be adapted to the strengths of the successful candidate, and appropriate methodological training will be provided.
Proficiency in a language other than English would be highly relevant, but it is not essential. We strongly encourage applications from people from linguistically diverse backgrounds and from groups that have historically been underrepresented in science.
Eligibility
Applicants must meet UQ's requirements for admission to the Doctor of Philosophy program, including the University's academic and English-language requirements. Prospective candidates should consult the official website before applying.
How to express interest
Prospective applicants should first contact: Associate Professor Tatsuya Amano (t.amano@uq.edu.au).
Please include the following in your initial email:
- a current academic CV, including details of any publications, awards, and other relevant outputs;
- academic transcripts;
- a brief description of your relevant research experience and skills; and
- a recent writing sample, such as a published paper or research project report.
Shortlisted candidates will be invited to discuss possible research questions and scholarship competitiveness before submitting a formal expression of interest to UQ.
Funding and scholarships
Competitive scholarships are available to eligible domestic and international applicants through the UQ Graduate Research School Scholarships.
Both domestic and international students may be considered. These scholarships are competitive, with assessment considering academic performance, evidence of research capability, project quality, the research environment and the proposed advisory team.
Please do not submit an EOI unless you have been invited to an interview by the supervisor. Scholarship applications are assessed within specified rounds and are subject to fixed deadlines. The closing date for international applicants seeking to commence in Research Quarter 4 2027 or early 2028 will be 19th October 2026. The next round for domestic applicants will open in February 2027.
Funding Notes
Competitive scholarships are available to eligible domestic and international applicants through the UQ Graduate Research School Scholarships.
Both domestic and international students may be considered. These scholarships are competitive, with assessment considering academic performance, evidence of research capability, project quality, the research environment and the proposed advisory team.
References
Amano, T. & Berdejo-Espinola, V. (2025). Language barriers in conservation: consequences and solutions. Trends in Ecology & Evolution, 40, 273–285. https://doi.org/10.1016/j.tree.2024.11.003
Amano, T. et al. (2023). The manifold costs of being a non-native English speaker in science. PLOS Biology, 21, e3002184. https://doi.org/10.1371/journal.pbio.3002184
Amano, T. et al. (2023). The role of non-English-language science in informing national biodiversity assessments. Nature Sustainability, 6, 845-854. https://doi.org/10.1038/s41893-023-01087-8
Amano, T. et al. (2021). Tapping into non-English-language science for the conservation of global biodiversity. PLOS Biology, 19, e3001296. https://doi.org/10.1371/journal.pbio.3001296
This is a Preview Listing…
You must sign in to see the full job description, and to apply.
Manage / Upgrade this job to a Full Job Listing.
Find Your Best Opportunity
Tell them AcademicJobs.com sent you!