The Machine Learning group at the University of Auckland is looking for a motivated PhD candidate and a Research Assistant to work at the interface between biosecurity, artificial intelligence and robotics. The goal of the project is to develop innovative, efficient and robust computational algorithms and tools for addressing pressing NZ biosecurity challenges. Particularly we aim to implement cost-effective real-time predator management systems that will work with minimal human oversight in vast wild and difficult to reach environments. Both positions are funded within the scope of the Biosecurity Technology Spearhead Research project that was recently launched by the The Science for Technological Innovation (SfTI) National Science Challenge Programme to develop new technology to support the Aotearoa-wide mission to eradicate NZ predators and pests by 2050.
This project offers a great opportunity for the candidate to carry out a genuinely transdisciplinary project with high commercialization potential and economic benefit to NZ. The candidate will benefit from the supportive research environment of the Machine Learning Group and UoA, but also the benefits of contacts, workshops and capacity development events offered by the SfTI Programme.
Equivalent of a New Zealand 1st class Honours degree or a MSc degree (both with a significant research component) in Computer Science, Data Science, Artificial Intelligence or related filed. Your research dissertation or thesis will have been awarded first class honours, or a strong upper second (B+). For the part-time RA position, students in their last year of the degree are welcome to apply.
Essential skills and personal attributes
Advanced programming skills, theoretical and practical knowledge in Machine Learning and Deep Leaning, data manipulation and search algorithms. Demonstrated ability to undertake self-directed research activities; Willingness and motivation to undertake cross-disciplinary research work. Excellent communication and written skills in English. Ability to present work to a diverse audience and projects partners, and document work in technical reports (relevant for the RA position).
Preferred skills/Ideal candidate
Experience with deep learning for video/image classification; data augmentation; semi-supervised learning; swarm intelligence or/and AI planning methods.
1 March 2022 (can be negotiated)
PhD Scholarship Funding:
NZD $35,000 (base stipend + tuition fees) per annum for 3 years.
Research Assistant (RA) Funding:
Up to $65,000 per annum (depending on skills and experience) for 1,5 years. The position is available as a full time or part time (0.4 – 0.8 FTE) job.
The students will be supervised by Katerina Taskova.
The application should include your academic transcripts, a CV (complete with the names and contact details of two referees), a PDF copy of your research dissertation or thesis (if available), and cover letter – a written statement of approximately 300 words outlining why this project interests you and how you meet the selection criteria.
Shortlisted candidates will be invited for an interview in person or virtual.
A successful candidate would be expected to go through the usual application process for doctoral studies.
Please refer to the following link on the requirements and application procedure for a PhD admission at UoA: https://www.auckland.ac.nz/en/study/study-options/find-a-study-option/doctor-of-philosophy-phd.html
The application closes on 15 February 2022, or as soon as suitable candidates are found.
If you have further questions or more details about the project feel free to contact Katerina Taskova (email@example.com).