Publisher
source

Emily Lines

Top university

4 months ago

Forest ecology University of Cambridge in United Kingdom

Degree Level

PhD

Field of study

Computer Science

Funding

PhD students are funded through competitive applications to Cambridge Trusts, GATES, and other structured PhD programmes. Funding typically covers stipend, tuition fees, and research costs. Only the strongest applicants are put forward for funding consideration. External funding sources may be available but must be discussed with the supervisor. Funding is highly competitive and not guaranteed.

Deadline

Expired

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Country

United Kingdom

University

University of Cambridge

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Keywords

Computer Science
Data Science
Environmental Science
Biology
Remote Sensing
Forestry
Geography
Artificial Intelligence
Rainforest Ecology
Ecological Modeling

About this position

PhD Positions in Forestry using Remote Sensing and Data Science

See below ??

Interested in a phd studying forests using remotesensing and datascience / AI ? Want to start Oct 26? Come work with us in Cambridge!

There is some general information and links on applying for PhDs in my group on my website ( https://lnkd.in/eBGUrQEJ ).

My group is focussed on highly computational approaches in forest ecology using data science/AI, as well as field techniques; I look for students with evidence of excellence in these areas. The deadline for funding is 2nd December (including references) - get in contact if you'd like to chat ??????

PS - reaching out to a PI can be daunting! I give some specific advice on how to do it well (for me at least) - here: https://lnkd.in/ddFFJze5

Funding details

PhD students are funded through competitive applications to Cambridge Trusts, GATES, and other structured PhD programmes. Funding typically covers stipend, tuition fees, and research costs. Only the strongest applicants are put forward for funding consideration. External funding sources may be available but must be discussed with the supervisor. Funding is highly competitive and not guaranteed.

What's required

Applicants should have strong computational and quantitative skills, with evidence of excellence in data science, AI, or related fields. A background in forest ecology or environmental science is preferred. Candidates must be interested in highly computational approaches and field techniques in forest ecosystems. Applications require a strong academic record and a clear ecological research focus. All applicants must apply for competitive funding and should contact the supervisor ahead of the deadline. English language proficiency and a relevant undergraduate or master's degree are expected.

How to apply

Contact Emily Lines informally ahead of the deadline to discuss your fit and research ideas. Prepare your CV and research proposal for feedback. Submit your formal application through the University of Cambridge system before the deadline. Review the group website and application advice for details.

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