Laboratory for Brain and Machine Intelligence

Laboratory for Brain and Machine Intelligence @ KAIST

Laboratory for brain and machine intelligence, KAIST

Current openings

- Graduate students
- Undergraduate research
- One postdoc position (computational neuroimaging; UCL-based) : filled
- One researcher position : currently open
(See below for more details)

Graduate students in machine learning and/or computational neuroscience

Bio and Brain Engineering (BBE) : We are seeking qualified candidates who are interested in computational neuroscience and/or brain-inspired AI.

Brain and cognitive engineering program (BCE program): We do NOT accept students unless exceptionally qualified.

Undergraduate research opportunities

Individual study, graduate study, and internships are available. If interested, send an email to
(1) a brief statement about your research interest and
(2) a transcript.

*URP program : if you were successful in the individual study, you may apply for the URP.

*Research topics (examples)
- deep learning + meta BCI (on EEG data)
- multi-agent reinforcement learning (AI soccer simulation)
- model-based deep reinforcement learning simulation
- model-based fMRI analysis (GLM, MVPA, DCM)
- exploring neural space via fast matrix computation (CovGram)
- deep learning-based experimental design (Deep neural experimenter)
- large-scale computational modeling on behavior data

Postdoctoral position (AI and/or computational neuroscience)

One postdoctoral position, funded through Samsung future technology foundation, is immediately available in the Laboratory for Brain and Machine Intelligence, led by Sang Wan Lee, at KAIST ( The laboratory is affiliated with the department of bio and brain engineering, brain and cognitive engineering program, and KAIST Institute for Artificial Intelligence (KIAI) and KAIST Institute for Health Science and Technology (KIHST).

The position is initially appointed for one year, and may be extended for up to three years. We offer a competitive salary plus benefits. We also provide opportunities for working with our collaborators.

The project, AI-human coevolution engine, aims to develop a framework that boosts human learning and inference performance. It requires a combination of model-based neuroimaging techniques and a design of various learning algorithms. Research topics include model-based/model-free reinforcement learning, inductive/deductive/transitive inference, and one-shot learning. Details about the project is confidential, but the research proposal will be outlined during an interview.

Qualifications (type1):
- PhD in cognitive neuroscience, computational neuroscience, or physics
- prior experience in (model-based) fMRI analysis is preferred.

Qualifications (type2):
- PhD in electrical engineering, computer science, or applied mathematics
- strong quantitative background with expertise in stochastic neural network, deep learning, or reinforcement learning simulation

The positions are open until filled. Interested please send a cover letter, a CV and a list of two references to Applications will be reviewed on a rolling basis.

Researcher position

- BS or MS degree in CS, EE, and etc.
- Programming skill is preferred.

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