Job responsibilities:
Carry out research that enables AI Transportation, and develop industrial applications of the following research areas:
Machine learning/deep learning/reinforced learning algorithms, including statistical machine learning models, efficient neural networks, representation learning, self-supervised learning, graph representation learning, adversarial learning, multimodal and large-scale pre-training;
Decision-making optimization in autonomous driving, V2X and smart transportation systems, using reinforcement learning, multi-agent learning, and large-scale optimization;
Intelligent information retrieval, such as ranking, neural information retrieval, recommendation systems, user mining and modeling.
Qualifications and requirements:
Candidates should be graduates from well-known universities with a degree in computer science, electronic engineering, automation, transportation, applied mathematics, pattern recognition, artificial intelligence, or other related majors;
Candidates should have at least three years of working experience at renowned research institutes, or leading companies, in related fields;
Candidates should have academic or industrial experience in autonomous driving, V2X, or smart transportation system building;
Candidates should be proficient in NLP/ML/DL models and algorithms (e.g. GBDT/MLP/CNN/RNN/LSTM/Transformer), and familiar with reinforcement learning algorithms;
Candidates should be skilled in one or more mainstream deep learning frameworks (Caffe, TensorFlow, PyTorch, PaddlePaddle), and familiar with their architecture and implementation mechanisms;
Candidates should have extraordinary abilities in identifying and solving key research problems, with strong communication and teamwork skills.
Benefits:
Contact Us
Please send your resume toairhr@tsinghua.edu.cn.