Post-Doctoral Associate - Human Cognitive Neuroscience, Computational Psychiatry, and Brain Sti
Listed on 2026-06-19
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Research/Development
Research Scientist, Neurology, Data Scientist, Clinical Research -
Healthcare
Neurology, Data Scientist, Clinical Research
Position Summary
The Post-Doctoral Associate will join an interdisciplinary research program focused on understanding the neural circuit mechanisms underlying cognition and psychiatric illness. The successful candidate will lead analyses of human intracranial electrophysiology, behavioral, and brain stimulation datasets; develop computational models of neural and behavioral processes; contribute to experimental design; and disseminate findings through publications and conference presentations. This position provides a unique opportunity to work with rare human intracranial datasets and advanced neuromodulation approaches while developing an independent research trajectory in systems, cognitive, or clinical neuroscience.
Work schedule:
in-person (hybrid flexibility possible), Monday-Friday and weekends.
- 40% – Research and Data Analysis:
Analyze human behavioral, electrophysiological, neuroimaging, and brain stimulation datasets; develop computational models of cognition, behavior, and neural activity. - 25% – Experimental Design and Study Execution:
Design, implement, and oversee cognitive neuroscience and neuromodulation experiments; contribute to protocol development and data collection efforts. - 20% – Manuscript and Grant Preparation:
Lead and contribute to scientific publications; assist with grant writing and development of new research initiatives. - 10% – Mentorship and
Collaboration:
Mentor graduate students, research staff, and trainees; collaborate with investigators across psychiatry, neurosurgery, neuroscience, engineering, and psychology. - 5% – Scientific Dissemination:
Present research findings at conferences, seminars, and collaborative meetings.
- PhD, MD/PhD, or equivalent doctoral degree in neuroscience, psychology, cognitive science, biomedical engineering, computer science, psychiatry, neurology, statistics, or a related field.
- Strong quantitative and programming skills.
- Experience analyzing human behavioral, electrophysiological, neuroimaging, or other complex biological datasets.
- Demonstrated scholarly productivity through publications, preprints, or equivalent research outputs.
- Strong written and verbal communication skills.
- Ability to work independently and collaboratively in a multidisciplinary research environment.
- Experience with intracranial EEG, ECoG, stereo-EEG, DBS recordings, or neural stimulation studies.
- Expertise in computational modeling, including reinforcement learning, Bayesian methods, drift-diffusion models, or state-space approaches.
- Experience with Python, MATLAB, R, Julia, or related scientific computing tools.
- Familiarity with human cognitive neuroscience experiments and task design.
- Experience with neuromodulation methods including TMS, tACS, DBS, or responsive neurostimulation.
- Interest in computational psychiatry, addiction, depression, chronic pain, or related translational neuroscience research.
Pay Range: $63,480 – $74,424 annually (dependent on education, qualifications, and experience).
- Competitive wages, paid holidays, and generous time off.
- Continuous learning opportunities through professional training.
- Medical, dental, and pharmacy plans.
- Health care and dependent care flexible spending accounts.
- University HSA contributions.
- Disability and life insurance.
- Employee wellbeing program.
- Financial counseling services.
Employee Assistance Program with eight counseling sessions at no cost.
The University recognizes and values the importance of diversity and inclusion in enriching the employment experience of its employees and in supporting the academic mission. The University is committed to attracting and retaining employees with varying identities and backgrounds. The University of Minnesota provides equal access to and opportunity in its programs, facilities, and employment without regard to race, color, creed, religion, national origin, gender, age, marital status, disability, public assistance status, veteran status, sexual orientation, gender identity, or gender expression.
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