Regulatory Genomics Scientist, Brain Health Tools

Allen Institute; Seattle (WA); Hybride; USD 87 000 - 108 000; Plein temps

Résumé du poste

Allen Institute seeks a Scientist I to advance regulatory biology within a brain-health platform. You will convert cross-species single-cell multiomic data into training sets, analyze whole-brain enhancer screens, and work with ML colleagues to shape design objectives for in‑vivo validation.

You should have a PhD in a relevant field, experience with enhancer screens, and Python or R proficiency to drive sequence-based analyses and model interpretation.

Qualifications

• PhD in genomics or related field with strong publication record.
• Experience with single-nucleus multiomic, spatial, methylation, or 3D genome data.
• Proficiency in Python or R for large datasets; familiarity with sequence-based DL/AI tools.

Responsabilités

• Curate training, validation, and benchmark sets from cross‑species single‑nucleus multiomic data.
• Define cell-type targets and design objectives for synthetic enhancers from whole-brain single-cell atlas data.
• Apply sequence-to-function models and guided optimization to prioritize candidate enhancers, interpreting motif content, syntax, and spacing.
• Plan each design-and-test cycle with experimental colleagues, setting success criteria in advance and feeding screening results back into model training.
• Publish and present findings, openly releasing validated sequences, benchmarks, and documentation.

Connaissances

Python or R

Genomics data analysis

Regulatory genomics knowledge

Cross-disciplinary collaboration

Formation

PhD in genomics/computational biology/neuroscience/genetics or related field

Experience with single-nucleus multiomic or spatial methylation or 3D genome data

Publication record in gene regulation or regulatory genomics

Outils

Enformer

Borzoi

ChromBPNet

Description du poste

Allen Institute seeks a Scientist I to advance regulatory biology within a brain-health platform. You will convert cross-species single-cell multiomic data into training sets, analyze whole-brain enhancer screens, and work with ML colleagues to shape design objectives for in‑vivo validation.

You should have a PhD in a relevant field, experience with enhancer screens, and Python or R proficiency to drive sequence-based analyses and model interpretation.