Job description
MIT invites applications for a full-time Senior Academic Researcher to join our interdisciplinary team focused on cutting-edge research in neuroscience, cognitive science, and computational modeling. The successful candidate will lead ambitious investigations, shape project direction, analyze complex data, and contribute to the dissemination of findings through publications and talks. This role offers substantial opportunities for mentorship, collaboration, and grant development in a leading research environment.
The ideal candidate thrives in a collaborative setting, demonstrates strong scientific leadership, and is committed to advancing knowledge through rigorous experimentation and education.
Responsibility
- Lead and manage cutting-edge research projects in neuroscience and computational modeling, from experimental design to data interpretation.
- Develop and optimize novel experimental protocols, data collection pipelines, and statistical analyses.
- Collaborate with cross-disciplinary teams to integrate behavioral, neuroimaging, and computational data.
- Mentor and supervise graduate students, postdocs, and research staff; provide ongoing feedback and career development.
- Prepare, write, and submit grant proposals; manage project budgets and timelines.
- Publish results in high-impact peer-reviewed journals and present findings at national and international conferences.
- Ensure rigorous research practices, data governance, reproducibility, and adherence to ethical standards.
Qualification
- PhD in Neuroscience, Computer Science, Psychology, Bioinformatics, or a closely related field.
- 3-5+ years of postdoctoral or equivalent research experience with a strong publication record.
- Proficiency in Python and R for data analysis; experience with MATLAB or similar tools is a plus.
- Expertise in experimental design, statistical modeling, and data-driven methodologies; familiarity with machine learning methods is desirable.
- Demonstrated grant-writing experience and a history of securing external funding is preferred.
- Excellent written and verbal communication skills; ability to mentor students and collaborate across disciplines.
- Strong organizational skills, attention to detail, and commitment to reproducible research.