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Sebastian Leuzinger

2 months ago

Fully funded PhD in Plant Ecophysiology, Sensor Development, and Neural Networks at Auckland University of Technology Auckland University of Technology in New Zealand

Degree Level

PhD

Field of study

Computer Science

Funding

The position is fully funded for three years, covering tuition fees and a living allowance of approximately NZD 35,000 per annum, plus generous research funding. Student support, on-campus accommodation, student associations, and gym access are offered.

Deadline

Mar 31, 2026

Country flag

Country

New Zealand

University

Auckland University of Technology, New Zealand

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Where to contact

Official Email

Keywords

Computer Science
Environmental Science
Electrical Engineering
Biology
Plant Physiology
Artificial Neural Network
Machine learning

About this position

A fully funded PhD position is available in the group of Professor Sebastian Leuzinger at Auckland University of Technology (AUT), New Zealand, starting May 2026. The research is highly interdisciplinary, combining plant biology, engineering, and neural networks to develop novel sensors for monitoring tree transpiration and fluid transport. The project is hosted by AUT's School of Science and School of Engineering, Computer, and Mathematical Sciences, and involves collaboration with experts in New Zealand and overseas.

The successful candidate will work on developing and applying electronics engineering, sensor development, plant ecophysiology, environmental measurements, machine learning, and finite element models. The position is fully funded for three years, with tuition fees and a living allowance of approximately NZD 35,000 per annum covered, plus generous research funding. AUT offers a supportive environment with student support, on-campus accommodation, student associations, and access to a gym.

Applicants must hold an MSc, ME, or equivalent degree and have a strong background in one of the following areas: plant ecophysiology/environmental measuring techniques, electrical engineering and sensor development, or neural networks/finite element models. Advanced programming skills in Matlab, Python, or R, and software project management experience are required. Excellent English language skills and readiness to quickly learn new skills outside the candidate's background are expected. Peer-reviewed publications are an advantage. The role requires readiness to travel within New Zealand and work in a collaborative, interdisciplinary team.

To apply, candidates should send a cover letter and CV combined in a single PDF to Prof. Sebastian Leuzinger ([email protected]). The first page should include a small table with nationality, number of peer-reviewed publications, and name of university of previous degree. The application deadline is 31 March 2026 at 5pm.

This opportunity is ideal for candidates interested in plant ecophysiology, sensor development, neural networks, and interdisciplinary research at a leading young university. For further information, contact Prof. Sebastian Leuzinger at the provided email address.

Funding details

The position is fully funded for three years, covering tuition fees and a living allowance of approximately NZD 35,000 per annum, plus generous research funding. Student support, on-campus accommodation, student associations, and gym access are offered.

What's required

Applicants must hold an MSc, ME, or equivalent degree with a strong background in one of the following: plant ecophysiology/environmental measuring techniques, electrical engineering and sensor development, or neural networks/finite element models. Excellent English language skills, advanced programming skills (Matlab, Python, R), and readiness to quickly learn outside their background are expected. Peer-reviewed publications are an advantage. Applicants should be prepared to travel within New Zealand and collaborate with experts locally and internationally.

How to apply

Send a cover letter and CV combined in a single PDF to Prof. Sebastian Leuzinger. On the first page, include a small table with nationality, number of peer-reviewed publications, and name of university of previous degree. Email applications to [email protected].

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