About this role

Driving data pre-processing including checking labels, formatting, etc.
Support project team in building data pipelines for training deep neural networks.
Benchmarking and reporting of various neural network models performance.
Research into suitable new network architectures to for time series prediction, and anomalies detection.
Research into suitable new network architectures to improve the perception of the environment with a focus on optical sensors.
Research on supervised and unsupervised learning methods to estimate road participants' depth, motion, and velocity.
Research on various neural networks for the interpretation of camera images (object detection, panoptic segmentation) and trajectory/motion planning.
Fusion of different neural networks to use shared resources to decrease memory and computation footprint.

Must be enrolled at a University/College or Graduation date must be within the last six months in a Masters or PhD program.
Must have a cumulative GPA of at least 3.0.
Strong Python programming skills.
Good experience using Linux.
Experience with deep learning frameworks such as TensorFlow and PyTorch.
Good knowledge of image processing and machine learning.
Independent work, initiative, motivation, ability to work in a team.

Machine Learning Fellowship, 6-12 months

Key skills