PhD in Computer Science or related field, or master's degree with equivalent experience
Experience with sequence analysis and generative AI, especially in vision and language
Track record of research, including first-author publication in top-tier AI conferences
Proficiency in Python programming language
Familiarity with deep learning frameworks such as PyTorch or TensorFlow
Experience in robotics, particularly in planning, decision-making, control, or ROS usage
Knowledge of large-scale datasets, sensor data, transformer architectures, diffusion models, imitation and reinforcement learning algorithms is beneficial
Responsibilities
Collaborate with researchers to address real-world challenges in Embodied AI
Develop cutting-edge approaches for a variety of Embodied AI applications
Translate mathematical models into efficient, executable code
Conduct evaluations and empirical studies on robotic platforms in simulations and real environments
Propose significant intellectual properties and contribute to high-impact research publications
Benefits
Opportunity to work on innovative projects in the rapidly evolving field of Embodied AI
Collaborative team environment with experienced researchers
Potential for career development through research publications and patents
Access to cutting-edge robotic platforms and applications
Engagement in a culture that values problem-solving and innovation
Full Job Description
About the job:
Working closely with a team of experienced researchers to solve real world challenges in the domain of Embodied AI.
Developing state-of-the-art approaches for Embodied AI applications. Directions include, but not limited to, generative AI, representation learning, foundation models, reasoning, planning, data generation and augmentation, reinforcement learning, and low-level control.
Translating mathematical problem definitions and model/solution specifications into efficient executable code.
Conducting evaluation and empirical studies using robotic platforms in both simulation and real-world.
Proposing high-impact intellectual properties (e.g., patents), and publishing or contributing to research papers in top-tier AI venues.
About the ideal candidate:
PhD degree in Computer Science or related fields or master's degree with comparable experience.
Prior experience in sequence analysis and generative AI, in particular vision and language.
Proven research record in AI by having at least one paper as the first author in top tier venues, such as NeurIPS, ICML, ICLR, CVPR, ICCV, ECCV, ICRA.
Proficiency in Python programming language.
Experience with one or more mainstream deep learning frameworks e.g. PyTorch, TensorFlow.
Experience in robotics applications, in particular decision-making, planning and control, or experience with real robot and ROS is an asset.
Experience with using large-scale datasets and sensor data, or with use of various transformer architectures and diffusion models is an asset.
Experience with imitation and reinforcement learning algorithms is an asset.
