Research Fellow in Artificial Intelligence

Updated: 3 months ago

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Research Fellow in Artificial Intelligence
  • Kelburn
  • Contract
  • Fri Nov 24 01:51:15 2023
  • 6562B

  • Are you looking for a 3-year fixed term contract within the Antarctic Research Centre and newly established Centre for Data Science and Artificial Intelligence?
  • Can you provide expertise particularly in machine learning, deep learning, explainable AI modelling and visualisation techniques
  • Do you have an interest in helping the CDSAI to achieve strategic collaborations with the ARC for climate change modelling?

Te Herenga Waka - About Our University

Te Herenga Waka - Victoria University of Wellington is a global-civic university with our marae at our heart. This iho draws off our heritage and is further defined by our tūrangawaewae, in particular Wellington, Aotearoa, and the Asia-Pacific, all of which are expressed in our position as Aotearoa New Zealand's globally ranked capital city university.

Our core ethical values are respect, responsibility, fairness, integrity, and empathy. These core ethical values are demonstrated in our commitment to sustainability, wellbeing, inclusivity, equity, diversity, collegiality, and openness. With, and as, tangata whenua, we value Te Tiriti o Waitangi, rangatiratanga, manaakitanga, kaitiakitanga, whai mātauranga, whanaungatanga, and akoranga.

Kōrero mō te tūranga - About the role

Te Herenga Waka - Victoria University of Wellington is currently recruiting a Research Fellow to join the Antarctic Research Centre [insert link to https://www.wgtn.ac.nz/antarctic] and the newly established Centre for Data Science and Artificial Intelligence [insert link to https://www.wgtn.ac.nz/cdsai] on a 3-year fixed term contract. The successful applicant will provide expertise in artificial intelligence, particularly in the area of machine learning, deep learning, explainable AI modelling and visualisation techniques, to the two groups. The Research Fellow will develop AI and machine learning modelling algorithms and tools to help the ARC achieve its goals by undertaking statistical projections of future ice sheet and ocean changes, investigating how the polar regions respond to future emissions trajectories over a range of timescales. This work is enabled by the NZ$13M “Our Changing Coast” Programme [insert link to https://www.searise.nz/], and also connects with Projects 1 & 2 of the NZ$49M “Antarctic Science Platform” [insert link to https://www.antarcticscienceplatform.org.nz/]. The Fellow will also help the CDSAI to achieve strategic collaborations with the ARC for climate change modelling.

Key Responsibilities: 

  • Conceptualise and develop a machine learning framework to apply to Greenland and Antarctic ice sheet and ocean simulations.
  • Apply the trained model to Greenland and Antarctic ice sheet and ocean simulations to improve future projections.
  • Share and communicate results with other researchers.

The successful applicant will help to develop and employ new cutting-edge machine learning applications to deliver far more sophisticated and detailed insights into the potential future Greenland and Antarctic ice sheet contributions to global sea level than is currently possible using process-based models. As an expert in artificial intelligence, the successful applicant will work with our team of process modellers (ice-sheet, ocean, and atmosphere) and a team in CDSAI to 1) develop and train machine learning (ML) algorithms on satellite observational datasets, as well as on the outputs of process-based models to predict environmental outcomes under 'unknown' future scenarios; 2) use in situ observations of ocean temperature, salinity, and ice-shelf melt rate as training data to produce an optimized melt scheme for process-based ice sheet/shelf models; 3) employ the previously learned models with high-resolution ocean data, for example, to capture the influence of eddies in transfer heat across the continental shelf.

The research will involve supervised, unsupervised and transfer learning paradigms to automatically learn models that are interpretable to human experts. The experiments will be carried out on Grid-Computing and high-performing GPU resources, which CDSAI will provide. Full funding will also be providing to enable the successful applicant to recruit a dedicated Ph.D student to work on aligned projects.

Ō pūmanawa - About you

The successful applicant will help to develop and employ new cutting-edge machine learning applications to deliver far more sophisticated and detailed insights into the potential future Greenland and Antarctic ice sheet contributions to global sea level than is currently possible using process-based models. As an expert in artificial intelligence, you will work with our team of process modellers (ice-sheet, ocean, and atmosphere) and a team in CDSAI to 1) develop and train machine learning (ML) algorithms on satellite observational datasets as well as on the outputs of process-based models to predict environmental outcomes under 'unknown' future scenarios; 2) use in situ observations of ocean temperature, salinity, and ice-shelf melt rate as training data to produce an optimized melt scheme for process-based ice sheet/shelf models; 3) employ the previously trained models with high-resolution ocean data, for example, to capture the influence of eddies in transfer heat across the continental shelf.

Key Requirements:

  • PhD either in artificial intelligence, machine learning, applied statistics, computer science, data science or in the physical sciences (e.g. ice-sheet and/or climate modelling) with a significant computational and computer programming component.
  • Demonstrated practical experience setting up and running machine learning/statistical models, preferably for physical science applications.
  • Proven skills in presenting results to a wide range of audiences, including peer-reviewed publications.

Ētahi kōrero hai āwhina i a koe - Why you should join our team

Our team is fast paced, likes sharing ideas, and working in a collaborative style. We offer you flexible working arrangements, learning & development programs for Te reo Māori, and the opportunity to be part of two successful and dynamic research groups. You will join an existing group of reseach fellows in the National Modelling Hub[insert link to https://modellinghub.github.io/], a multi-institutional, multi-disciplinary centre hosted by Victoria University of Wellington, but also work closely with researchers in the CDSAI. The CDSAI is co-located with the School of Engineering and Computer Science and also School of Mathematics and Statistics, which have the first and the largest postgraduate AI programmes and the sole undergraduate AI major in New Zealand. This is a fantastic opportunity for someone who wants to develop expertise in AI and machine learning techniques for modelling climate change.

Role Description

Salary Range: $83,776 - $99,221 per annum

Close Date for Vacancy:8 December 2023

Contact Details for Vacancy: If you have any questions regarding this role, please get in touch with Prof. Nicholas Golledge ([email protected]). But applicants should follow all steps listed below.

Important - Application Steps and information

Download and complete the University Application Form .

Then, please combine your cover letter, CV and the University Application Form into a single file (preferably in pdf format).

Click Apply Now Button at the base of the advert. Follow the process to enter your contact details and attach your combined file (CV, cover letter and the University application form) using the “CV/Resume” button.

If you have any issues uploading your application, please email the completed application form, cover letter and CV to [email protected] stating the reference number and position title from the advert in the subject line.


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