Scientist I — Neuromodulation: Multimodal Data

Allen Institute; Washington (District of Columbia); On-site; USD 86,000 - 107,000; Full time

Benefits offered by this job

Relocation assistance

Visa sponsorship available

Benefits package

Job summary

The Allen Institute seeks a Scientist I to join the Neuromodulation team and lead multimodal data integration across neuromodulation datasets, uniting transcriptomics, morphology, and connectivity to map neuromodulatory cell types in the mouse brain.

You will develop and apply ML and statistical methods in close collaboration with experimental and computational teams to produce foundational knowledge and openly shared datasets for the structure and function of neuromodulation.

Qualifications

• PhD in Genomics, Neuroscience, Applied Mathematics, Electrical Engineering, Physics, or related field
• High proficiency in Python and R
• Strong grounding in mathematical and statistical methods
• Deep familiarity with agentic workflows for data analysis

Responsibilities

• Lead the project’s multimodal integration and analysis efforts
• Develop and devise conceptual and quantitative frameworks for multimodal data
• Conduct in-depth analyses and modeling of neuronal morphology
• Integrate transcriptomic, morphological, and connectivity data
• Collaborate closely with experimentalists and computational scientists
• Communicate progress and present findings to internal stakeholders and the scientific community
• Draft reports and manuscripts

Skills

Python

R

Mathematics

Statistics

Data analysis

Education

PhD in Genomics, Neuroscience, Applied Mathematics, Electrical Engineering, Physics, or related field

Job description

The Allen Institute seeks a Scientist I to join the Neuromodulation team and lead multimodal data integration across neuromodulation datasets, uniting transcriptomics, morphology, and connectivity to map neuromodulatory cell types in the mouse brain.

You will develop and apply ML and statistical methods in close collaboration with experimental and computational teams to produce foundational knowledge and openly shared datasets for the structure and function of neuromodulation.