[PhD Studentship in Environmental Intelligence – Fully Funded Doctoral Position]

RFCSR; Exeter; On-site; GBP 16,000 - 18,000; Full time

Benefits offered by this job

Fully funded

UKRI stipend

Tuition fees covered

Job summary

The University of Exeter offers a fully funded PhD studentship in Environmental Intelligence, combining environmental science, data science, and AI. The successful candidate will undertake research at the interface of these fields and contribute to interdisciplinary initiatives across the university.

The doctoral researcher will conduct independent research, participate in training, develop predictive models or ML methods, and contribute to publications while benefiting from a UKRI stipend and

Qualifications

• First-class or strong upper second-class honours in Environmental Science, Data Science, Computer Science or related field.
• Master's degree in a relevant field desirable but not essential.
• Strong academic potential and interest in interdisciplinary environmental research.

Responsibilities

• Conduct independent research in environmental intelligence.
• Engage with training, seminars and interdisciplinary initiatives.
• Contribute to academic publications and present findings.

Skills

Data analysis

Modelling

Programming (Python/R)

Communication

Education

Bachelor's degree in a relevant field

Master's degree desirable

Tools

Python

R

Job description

[PhD Studentship in Environmental Intelligence - Fully Funded Doctoral Position]

University of Exeter

Exeter, United Kingdom

[General Description – include all relevant details from the source]

The University of Exeter is offering a fully funded PhD studentship in Environmental Intelligence, providing an opportunity to engage in interdisciplinary research at the interface of environmental science, data science, and artificial intelligence. This studentship is aligned with Exeter’s strategic focus on addressing global environmental challenges through innovative, data-driven approaches.

The successful candidate will undertake a research project that leverages advanced analytical, computational, and modelling techniques to better understand and respond to complex environmental systems. Research may involve working with large-scale environmental datasets, developing predictive models, and applying artificial intelligence or machine learning methods to address issues such as climate change, biodiversity loss, or sustainable resource management.

The doctoral researcher will be part of a dynamic research environment, collaborating with leading academics and potentially external partners. Responsibilities include conducting independent research, participating in training and development programmes, contributing to academic publications, and engaging with seminars and interdisciplinary initiatives across the university.

This studentship supports cutting-edge research aimed at delivering real-world impact and advancing knowledge in environmental intelligence.

[Eligibility Criteria]

Applicants should hold, or expect to obtain, a first-class or strong upper second-class honours degree in a relevant subject such as Environmental Science, Data Science, Computer Science, Mathematics, or a related discipline. A Master’s degree in a relevant field is desirable but not always essential. Candidates must demonstrate strong academic potential and an interest in interdisciplinary environmental research. Applicants must meet the University of Exeter’s English language requirements where applicable.

[Required expertise/skills]

• Background in environmental science, computational science, or a related field
• Experience or interest in data analysis, modelling, or machine learning techniques
• Strong quantitative and analytical skills
• Ability to work with large and complex datasets
• Programming skills (e.g., Python, R, or similar) are desirable
• Strong written and verbal communication skills
• Ability to work independently and collaboratively within interdisciplinary teams

[Salary details]

The studentship includes full tuition fees and a stipend at the UK Research and Innovation (UKRI) rate. Additional funding may be available for research costs and training.

[Application Deadline]

Not explicitly specified in the provided source