Cirta is a new machine-learning challenge for high-energy physics on Zindi, the Africa-based data-science challenge platform. Launched this autumn at the International Conference on High Energy and Astroparticle Physics (TIC-HEAP), Constantine, Algeria, Cirta challenges participants to provide machine-learning solutions for identifying particles in LHC experiment data.

Physicists from the ATLAS, CMS and LHCb collaborations have just launched the TrackML challenge – your chance to develop new machine learning solutions for the next generation of particles detectors.

The dataset from the ATLAS Higgs Machine Learning Challenge has been released on the CERN Open Data Portal.

The winner of the four-month long Higgs Machine Learning Challenge, launched on 12 May, is Gábor Melis from Hungary, followed closely by Tim Salimans from The Netherlands and Pierre Courtiol from France. They will receive cash prizes, sponsored by Paris-Saclay Centre for Data Science and Google, of $7000, $4000, and $2000 respectively. The three winners have been invited to participate at the Neural Information Processing Systems conference on 13 December in Canada.

It's been four weeks since the four-month long Higgs Machine Learning Challenge was announced. Almost 700 teams have signed up and more than 200 have beaten the in-house benchmark already.