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Bright minds called to solve a problem that’s vexed experts
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Cash, career opportunities and potential to save lives on offer
SYDNEY, AU / ACCESS Newswire / March 16, 2026 / When an asteroid slams into Earth, where does the debris land? Fragments of every size, shape, and density scatter across vast distances – and predicting where they end up is a problem that has vexed scientists for decades. The same challenge applies to any sudden, violent disruption: landslides, building collapses or avalanches.
Freelancer, the world’s largest freelancing and crowdsourcing marketplace, today announced the “Boom: Trajectory Unknown Challenge” – a global competition seeking breakthrough AI/ML solutions to predict where materials land after sudden, violent disruptions.
The challenge, part of Freelancer’s Moonshot Innovation Program, offers an US$7,000 prize for the team or individual that most effectively cracks this deceptively complex problem: creating machine learning algorithms that accurately predict the final resting place of scattered materials of different sizes, shapes, and densities.
“Imagine an asteroid impact where every second counts – emergency teams need to know where debris landed, where people might be trapped, or where critical infrastructure was struck,” said Freelancer Chief Executive Matt Barrie. “This is an opportunity to work on technology that could genuinely save lives – and be handsomely rewarded for your expertise.”
The Moonshot Innovation Program recently opened to all enterprises after a decade in which users submitted more than 20,000 entries to challenges set by NASA, NIH, and the CDC. The program’s growing roster of sponsors now includes the United Nations Development Programme, which partnered with Freelancer to crowdsource affordable solutions for detecting underwater explosive ordnance threatening communities in conflict and post-conflict zones worldwide.
The platform has helped NASA save 80-99% on R&D costs and compressed the U.S. Bureau of Reclamation’s river modeling from 72 hours to just 60 minutes. Winners of past Moonshot challenges have seen their solutions advance to spaceflight, secure additional R&D funding, and spin into commercial products.
The sponsoring organization – which is applying this technology to real-world scenarios – is seeking algorithms that don’t just work in controlled lab conditions but can generalize across messy, unpredictable environments where materials behave in complex, often surprising ways.
The Boom: Trajectory Unknown Challenge targets AI and Machine Learning engineers, computational physicists, and spatial data scientists who thrive on difficult problems. The winning entrant may also be offered a contract to continue developing their solution beyond the competition.
The Boom: Trajectory Unknown Challenge has now launched with submissions closing May 5, 2026, and winners announced June 3, 2026 (Australia time).
Registration and full details are available at https://www.freelancer.com/boom
For more information, contact:
Media Inquiries
Brent O’Halloran
Director of Communications
press@freelancer.com | +1 (650) 442 3334
About Freelancer
Thirteen-time Webby award-winning Freelancer is the world’s largest freelancing and crowdsourcing marketplace by total number of users and projects posted. More than 80 million registered users have posted over 25 million projects and contests to date in over 3,000 areas as diverse as website development, logo design, marketing, copywriting, astrophysics, aerospace engineering and manufacturing. Freelancer owns Escrow.com, the leading provider of secure online payments and online transaction management for consumers and businesses on the Internet with over US$8 billion in transactions secured. Freelancer also owns Loadshift, Australia’s largest heavy haulage freight marketplace with over 800 million kilometres of freight posted since inception. Freelancer Limited is listed on the Australian Securities Exchange under the ticker ASX:FLN and in the United States as FRLCY.
SOURCE: Freelancer
View the original press release on ACCESS Newswire
