Job responsibilities:
Carry out research that enables autonomous driving, V2X, and AI Transportation, produce influential research outcome, and promote industrial application 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;
Computer vision, including image classification, facial recognition, object detection, image segmentation, image recognition, image/video understanding, and model compression;
Machine learning systems, including distributed optimization methods for machine learning, federated learning, and efficient neural networks;
Intelligent information retrieval, such as ranking, neural information retrieval, recommendation systems, user mining and modeling;
Data mining, including data crowdsourcing, social network mining, large image modeling and analysis, and stream data computing;
Decision-making optimization, including reinforcement learning, multi-agent learning, and large-scale optimization.
Qualifications and requirements:
Candidates should hold a doctoral degree (within three years of graduation and under 35 years old, for post-doc positions) in computer science, electronic engineering, automation, transportation, applied mathematics, pattern recognition, artificial intelligence or other related majors;
Candidates should have internationally recognized academic achievements; or rich R&D experience in industry;
Candidates should have extraordinary abilities in identifying and solving key research problems, with strong communication and teamwork skills.
Salary and benefits：
World-class research environment, internationally competitive package, Tsinghua benefits;
Open and collaborative academic atmosphere, sufficient start-up funds;
Research platform at Tsinghua with abundant data and top-tier industrial resources;
Mature pipeline for technology industrialization and incubation.
Contact Us
Please send your resume toairhr@tsinghua.edu.cn.
