Scientist I: Multimodal ML for Brain Gene Regulation

Allen Institute

Seattle (WA)

Hybrid

USD 87,000 - 107,000

Full time

3 days ago
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Benefits offered by this job

Relocation assistance
Visa sponsorship

Job summary

The Allen Institute seeks a Scientist I to design modern ML methods for multimodal foundational models focused on gene regulation and Alzheimer’s disease pathology. You will build deep generative and Bayesian models, integrating omics, neuropathology, MRI, and clinical data in a highly collaborative team.

Strong candidates will have a PhD and a track record in computational biology, causal inference, or gene regulation in disease.

Qualifications

  • Ph.D. in a relevant field or equivalent experience.
  • Experience with modern deep learning architectures / foundational models.
  • Experience with Bayesian modeling and inference.
  • Experience developing causal models in biology or disease contexts.

Responsibilities

  • Design ML methods to integrate multimodal data and model disease trajectories.
  • Develop deep generative and Bayesian models for Alzheimer’s pathology.
  • Evaluate models for harmonizing data across cohorts and studies.
  • Create causal models of disease progression and validate them.
  • Stay at the forefront of AI for multimodal disease progression modeling.
  • Collaborate in a multidisciplinary environment and publish findings.
  • Present results at peer-reviewed journals and conferences.

Skills

DL architectures
Bayesian modeling
Causal inference
Multimodal data
Scientific publication
Collaborative work

Education

Ph.D. in Computer Science / Computational Biology / related

Job description

The Allen Institute seeks a Scientist I to design modern ML methods for multimodal foundational models focused on gene regulation and Alzheimer’s disease pathology. You will build deep generative and Bayesian models, integrating omics, neuropathology, MRI, and clinical data in a highly collaborative team.

Strong candidates will have a PhD and a track record in computational biology, causal inference, or gene regulation in disease.

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