Scientist - Integrative Analysis of SEA-AD and Community Multiomics Datasets

Scientist I – Integrative Analysis of SEA-AD and Community Multiomics Datasets

The mission of the Allen Institute is to understand the principles that govern life, and to advance health. Our creative and multi‑dimensional teams focus on answering some of the biggest questions in bioscience. We accelerate foundational research, catalyze bold ideas, develop tools and models, and openly share our science to make a broad, transformational impact on the world.

The Seattle Alzheimer’s Disease Brain Cell Atlas (SEA‑AD) consortium strives to achieve a deep molecular and cellular understanding of the early pathogenesis of Alzheimer’s disease (AD). Leveraging advances in quantitative neuropathology and next‑generation single cell molecular profiling technologies, we are generating large‑scale data sets from well‑characterized donors that span the spectrum of AD pathology to comprehensively map human brain cell types across aging and disease.

These data, along with tools for their use, are made freely and publicly available.

We seek to hire a Scientist to integrate, analyze, and interpret single‑nucleus multiomics datasets from the broader research community in conjunction with SEA‑AD datasets. Community datasets will include those from other AD and AD/ADRD donor cohorts as well as animal models. This position will leverage existing computational tools and develop novel pipelines and approaches to analyze and interpret these data. This position is part of SEA‑AD’s Integrative Analysis Center (IAC) and will collaborate with a dynamic team of quantitative and experimental scientists to build an integrated resource that defines how cell types are affected in AD and AD/ADRD across community datasets.

The goal of the IAC is to synthesize knowledge from the field and share it widely and coherently.

• Collaborate with SEA‑AD and SEA‑AD IAC members and outside investigators to ensure community multi‑omic datasets are re‑processed, their metadata is harmonized, and relevant secondary data types are obtained (e.g. whole genome sequencing, nuclear imaging, or blood‑based biomarkers).
• Adapt existing or develop novel computational tools to rigorously quantify changes in cell types in Alzheimer’s disease across community datasets.
• Associate gene expression and chromatin accessibility changes with relevant and available donor metadata or secondary data types.
• Compare cell type changes across disease progression between study regions to identify common early changes that may inform biomarkers.
• Interact with scientists from diverse backgrounds and perspectives to design analytical approaches and refine computational strategies.
• Work with experimental scientists to design experiments to validate predictions of disease function.
• Participate in a highly interactive and multidisciplinary environment.
• Publish and present findings in peer‑reviewed journals and scientific conferences.

• Ph.D. in Neuroscience, Computational Neuroscience, Computer Science, Applied Math, or a related field; or equivalent combination of degree and experience.
• Fluency programming in Python and high performance computing.
• Fluency with version control systems (e.g. Git/Github).
• Familiarity with analysis of RNA‑sequencing or related data types.

• Experience with modeling disease or developmental trajectories, or related computational studies.
• Additional experience in computational analysis and statistical assessment of biological datasets in other modalities such as spatial statistics, ATAC‑seq analysis, computational anatomy, or related fields.
• Previous work on studying Alzheimer’s disease or other neurodegenerative diseases.
• Familiarity with additional programming languages (e.g., R).
• Experience with GPU‑based deep learning.
• Ability to work effectively in a highly collaborative environment.
• Strong written and verbal communication skills.
• Ability to work independently and collaboratively.
• Strong publication track record.

• Occasional lifting up to 30 pounds.
• Fine motor movements in fingers/hands to operate computers and other office equipment; repetitive motion with lab…