Jana Makar

Stock image of light patterns.

Simulating quantum systems

"By investigating our code and optimising the libraries that we were using, the NeSI consultants sped up components of our code by a factor of 20."
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Upon the recent release of a post-event report of Indigidata Aotearoa 2023, a groundbreaking wānanga aimed at advancing Indigenous data science and sovereignty, we wanted to take a moment to reflec... Read more

From 19-22 February 2024, NeSI team members attended the SuperComputing Asia 2024 conference, held for the first time in Australia.This was a wonderful opportunity to learn from peer experiences ac... Read more

The eResearch NZ | eRangahau Aotearoa 2024 conference ran from 7-9 February in Wellington and brought together hundreds of brilliant minds working to make a difference to our world. Together we lea... Read more

Please join us in welcoming the newest member to the NeSI team! Attribution: Shingo Aoyama, DevOps and Integration ProgrammerRaised in the suburbs of Auckland, I completed my conjoint degree in Com... Read more

A picture of someone sitting in a cave in French Polynesia.

Understanding future climate change through the lens of past climates

"The support received from NeSI significantly contributed to our research capabilities and productivity."
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New Zealand eScience Infrastructure (NeSI) is refreshing its technology platform to ensure Aotearoa's national eResearch infrastructure and services are more accessible, responsive, and flexible to... Read more

On Tuesday 27 February the World Data Systems' Early Career Researcher (ECR) Network is hosting a webinar to share the firsthand experiences of its ECR Network co-chairs – Maja Dolinar, Claire Rye,... Read more

Figure: Surface air temperature (deg. K) modelled in the Ross Sea region of Antarctica

Building software solutions for studying air–ice–ocean interactions

"We are very grateful to the NeSI team for helping us to automatically build our coupled model in a container, allowing us to be resilient and circumvent any platform changes/updates."
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Results from ML-based exploration of optical rotation prediction, with the identification of influential dihedral angles highlighted in the molecular structure on the right.

Applying machine learning to uncover molecular property insights

"I appreciate their methodical approach and the computational tools they were able to introduce to the project, which were essential in enabling the research."
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