The Damisah lab at Yale University is currently recruiting highly motivated postdoctoral scholars who work with intracranial EEG and single-unit recordings to join our research team. Our lab is composed of scientists from various academic backgrounds, including neuroscience, bioengineering, computer science, and psychology. We aim to create a supportive environment for innovative and rigorous scientific research, as well as personal and professional development of all our members. We provide access to cutting-edge facilities and excellent opportunities for collaboration with neurology, psychiatry, psychology, and neuroscience at the Yale School of Medicine.
Our lab is interested in understanding the neural mechanisms of human cognition, including various states of arousal, the neural correlates of interoceptive feedback during periods of heightened states of arousal, including the correlates of threat and emotional valence in humans.
Interested and qualified candidates should send a cover letter, CV, and representative publication(s) to [email protected].
Required Skills and Experience:
- A Ph.D. in psychology, neuroscience, engineering, computer science, or a related field is required.
- Proficient in MATLAB, Python, and/or R programming and data visualization experiences.
- Familiarity with time-frequency analysis in Fieldtrip, MNE, or similar environments.
Preferred Skills and Experience:
- Previous experience with human scalp/icEEG, single-unit recordings.
- A strong background in computational modeling of behavioral or neural data.
- Experience with statistics, machine learning, and/or brain stimulation.
Our project enables unparalleled access to various patient populations and a variety of complementary techniques: single and multi-unit neuron recordings, intracranial electroencephalogram, closed loop recording, and stimulating devices such as DBS, RNS, measures of the autonomic nervous system (heart rate, pupillometry). This invasive human electrophysiology-centric approach is combined with behavioral tasks, naturalistic behaviors, and computational modeling to ask fundamental questions about human cognition.