Research Scientist, Human inspired AI Responsibilities:
- Lead research to advance the science and technology of intelligent machines.
- Publishing state-of-the-art research papers in both high impact machine learning and cognitive science outlets.
- Conducting independent research that investigates how AI can improve the science of learning in biological organisms and vice versa.
- Work towards long-term ambitious research goals, while identifying intermediate milestones.
- Lead and collaborate on research projects within a globally based team.
- Open sourcing high quality code and reproducible results for the community.
Minimum Qualifications:
- Currently has, or is in the process of obtaining, a PhD in mathematics, statistics, computer science, cognitive or language science with a strong background in both theoretical and empirical disciplines.
- Deep interest in cross-disciplinary communication towards conducting research in human inspired AI.
- Experience with scalable machine learning systems, resource-efficient AI data and algorithm scaling, or neural network architectures.
- Experience communicating complex research for public audiences of peers.
- Experience with deep learning frameworks such as Pytorch, Jax, or Tensorflow.
- Must obtain work authorization in country of employment at the time of hire, and maintain ongoing work authorization during employment.
Preferred Qualifications:
- Proven track record of achieving significant results as demonstrated by grants, or fellowships, as well as publications in *ACL, top speech and language conferences and/or top cognitive (neuro)science journals.
- 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 solving analytical problems using quantitative approaches.
- Experience manipulating and analyzing complex, large scale, high-dimensionality data from varying sources.
- Experience in utilizing theoretical and empirical research to solve problems.
- Experience doing optimization 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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