The challenge of HAhRD project is to implement new algorithms to classify objects from 3D images-like coming from the data acquisition of the future sub-detector of CMS. This detector that contains about 6 million channels will be used to reconstruct the 3D clusters from hundreds of impinging particles arising from the proton-proton collisions within the Large Hadron Collider. The initial implementation based on an image processing algorithm is already exploited. We want in this proposal implement several Deep Neural Networks (DNN) architectures (in particular Convolutional Neural Networks - CNN) to classify clusters of points and develop a chain suite to analyze the classification performed by the DNN/CNN.
Good C++/C skills, good python skills, familiar with GPUs if possible and visualization tools. Knowledge on machine learning or image processing or statistics would be appreciated.