Post-Doctoral Associate - Human Cognitive Neuroscience, Computational Psychiatry, and Brain Sti[...]

University of Minnesota; Minneapolis (MN); On-site; USD 63,480 - 74,424; Full time

Benefits offered by this job

Competitive wages

Medical, dental, and pharmacy plans

Employee Assistance Program with eight counseling sessions at no cost

Job summary

The University of Minnesota is seeking a Post-Doctoral Associate to engage in research concerning neural circuits related to cognition and psychiatric illness. This role involves analyzing human intracranial datasets and developing computational models within a collaborative environment. Ideal candidates hold a PhD or equivalent and possess strong quantitative skills.

The position offers in-person work with some flexibility, competitive pay ranging from $63,480 to $74,424 annually, and numerous benefits including medical plans and professional development opportunities.

Qualifications

• PhD, MD/PhD, or equivalent in neuroscience, psychology, cognitive science, or related field.
• Experience with human behavioral and electrophysiological datasets.
• Ability to work independently and in multidisciplinary environments.

Responsibilities

• Analyze human behavioral and electrophysiological datasets.
• Design and oversee cognitive neuroscience experiments.
• Lead and contribute to scientific publications.

Skills

Strong quantitative and programming skills

Experience analyzing complex biological datasets

Strong written and verbal communication skills

Education

PhD, MD/PhD, or equivalent doctoral degree

Tools

Python

MATLAB

R

Julia

Job description

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.

Duties / Responsibilities

• 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.

Required Qualifications

• 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.

Preferred Qualifications

• 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 and Benefits

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.

Diversity and Inclusion

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. Learn more at http://diversity.umn.edu.

Employment Requirements

Any offer of employment is contingent upon the successful completion of a background check. Our presumption is that prospective employees are eligible to work here. Criminal convictions do not automatically disqualify finalists from employment.