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10 часов назад

AI Scientist (BioMedical AI)

212 000 - 265 000$
Тип работы
fulltime
Английский
b2
Страна
UK/US
Вакансия из списка Hirify.GlobalВакансия из Hirify Global, списка международных tech-компаний
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Описание вакансии

Текст:
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TL;DR
AI Scientist (BioMedical AI) (Foundation Models/Single-Cell Biology): Developing foundation models and scalable ML pipelines for large-scale perturb-seq and single-cell datasets with an accent on causal biological insight and multimodal integration. Focus on designing self-supervised architectures, integrating transcriptomic, epigenomic, and proteomic data, and collaborating with experimental biologists to identify therapeutic opportunities.

Location: South San Francisco, California, United States

Base salary: $212,000–$265,000 annually, plus bonus and equity.

Company

hirify.global is a biotech startup using generative AI and foundation models to advance drug discovery, design protein and antibody therapeutics, and improve target elucidation and patient stratification.

What you will do

  • Design, train, and refine foundation models for perturb-seq and other single-cell datasets.
  • Build scalable pipelines for preprocessing, normalization, and integration of large-scale biological data.
  • Apply machine learning to model cellular responses and identify causal biological insights.
  • Develop multimodal integration methods across transcriptomic, epigenomic, and proteomic readouts.
  • Collaborate with experimental biologists to align computational methods with experimental design and discovery goals.
  • Publish research methods and results in scientific journals and present at conferences.

Requirements

  • PhD or equivalent in computational biology, computer science, bioinformatics, or a related discipline.
  • Strong expertise in single-cell data analysis, particularly perturb-seq.
  • Hands-on experience with foundation models or large-scale self-supervised learning, including transformers or variational autoencoders.
  • Strong coding skills in Python and ML frameworks such as PyTorch or TensorFlow.
  • Experience with single-cell analysis tools such as Scanpy and Seurat.
  • Experience developing scalable ML methods for large biological datasets.

Nice to have

  • Background in causal inference, generative models, or representation learning for biological systems.
  • Familiarity with multi-omics integration and cross-modal foundation models.
  • Impactful publications in computational biology, machine learning, or related fields.

Culture & Benefits

  • Open, flexible, and friendly work environment.
  • Opportunities to develop a long-term scientific career.
  • Competitive benefits package with base salary, bonus, and equity.
  • Commitment to diversity and inclusion.

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