* Survey the Deep Learning and Deep Reinforcement literature to keep track of the latest advances in the field.
Survey the Deep Learning and Deep Reinforcement literature to keep track of the latest advances in the field.
Collaboratively decide which methods that we think are the most promising candidates for verification
Reproduce key published results, design and train novel SOTA models, explore new training techniques.
Improve upon the published results, integrate with other methods, incorporate into our code base
Strong algorithm and mathematical skills (Multivariable Calculus, Linear Algebra, Probability, Statistical Inference, Optimization)
Strong understanding of Deep Learning; proficient in training and evaluating state of the art Deep Networks for Classification, Semantic & Instance Segmentation, and Object Detection; exposure to 3D Deep Learning
Strong Python skills, proficient in Pytorch and or TensorFlow
Understanding of Machine Learning in general (exposure to RL, SVMs, Kernel Methods, Decision Forests, Logistic Regression, Clustering)
Masters in Computer Science (or related degree e.g. EE, Applied Math) or Equivalent Experience (min. 3 years)