Postdoctoral Researcher, Embodied AI (PhD)
Meta

Meta is seeking a Postdoctoral Researcher to join Meta Fundamental AI Research (FAIR), a research organization focused on making significant progress in AI. Individuals in this role are expected to be recognized experts in identified research areas such as artificial intelligence, machine learning, robotics, and embodied AI, particularly including areas computer vision, vision-language models, LLMs, agents, planning, and physical word understanding. Our postdoctoral researchers have opportunities to make core algorithmic and system advances and apply their ideas at an unprecedented scale. The ideal candidate should have a keen interest in producing new, open science to make embodied agents more intelligent.The mission of Meta FAIR's Agent research is to explore how to create general agents capable of understanding our physical and digital worlds and using this knowledge to take actions for you. These digital agents take actions by actuating UIs and making API calls to off load our daily digital chores. Some research directions of interest are: - Investigate algorithmic development and application of foundation models for digital agents- Representation learning for agent tasks- Developing simulation platforms for agent AI research (e.g. visual web arena)- Multimodal perception- Continual learning in interactive environments- Developing efficient models deployable to mobile devices and hardware

Postdoctoral Researcher, Embodied AI (PhD) Responsibilities:

• Perform fundamental and applied research to push the scientific and technological frontiers of embodied artificial intelligence.
• Invent/improve novel data-driven paradigms for embodied intelligence, including digital agents, AR, and VR, leveraging a variety of modalities (images, video, text, audio, tactile, etc).
• Develop algorithms based on state-of-the-art machine learning and neural network methodologies.
• Define, build and benchmark new capabilities needed for the next generation of AI.
• Conduct research towards long-term ambitious research goals while identifying intermediate milestones.
• Conduct research to advance the science and technology of intelligent machines.
• Conduct research that enables learning the semantics of data across multiple modalities (images, video, text, audio, speech and other modalities).

Minimum Qualifications:

• Currently has or is in the process of obtaining a PhD in the field of Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience. Degree must be completed prior to joining Meta.
• Experience with deep learning frameworks (such as pytorch, tensorflow) and Python.
• Research experience in Digital Agents, Vision Language Models, Computer Vision, LLMs, NLP, reinforcement learning and tool usage.
• Experience communicating research for public audiences of peers.
• Must obtain work authorization in the country of employment at the time of hire, and maintain ongoing work authorization during employment.
• Currently has, or is in the process of obtaining a Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience. Degree must be completed prior to joining Meta.

Preferred Qualifications:

• Proven track record of achieving significant results as demonstrated by grants, fellowships, patents, as well as publications at leading workshops, journals or conferences such as CVPR, ECCV, ICCV, NeurIPS, or SIGGRAPH.
• Demonstrated research and software engineering experience via an internship, work experience, coding competitions, or widely used contributions in open source repositories (e.g. GitHub).
• Experience with manipulating and analyzing complex, large scale, high-dimensionality data from varying sources.
• Experience building systems based on machine learning and/or deep learning methods.
• Experience solving complex problems and comparing alternative solutions, tradeoffs, and diverse points of view to determine a path forward.
• Experience working and communicating cross functionally in a team environment.

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