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Paid Internship
Work Mode
Time Spent
Required Degree
Duration

6Open Positions

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Research Scientist Intern

GenBio AI
Found 5 months ago
Location
Silicon Valley, United States
Duration (Months)
6 Months
Time
Not disclosed
Work Mode
Not disclosed
Salary
Not disclosed
Visa Help
Not disclosed
Last Verified
2 months ago

Education

  • Master
  • PhD

Skills & Qualifications

Technical Skills

  • deep learning methods/models
  • JAX
  • TensorFlow
  • PyTorch
  • generative models
  • graph neural networks
  • large-scale deep learning applications
  • statistics
  • optimization
  • graph theory
  • linear algebra
  • software engineering best practices
  • version control
  • documentation
  • AI
  • computational biology
  • AI/ML

Soft Skills

  • Passion for interdisciplinary research
  • willingness to acquire necessary domain knowledge
  • Motivated
  • self-driven
  • ability to operate with partial descriptions of high-level objectives

Job Description

You will work with the team to conduct cutting-edge AI and computational biology research. Your primary tasks will include improving existing models and exploring new methodologies to advance our AI capabilities in biology. You will work with the team on designing and executing experiments, analyzing complex datasets, and applying statistical techniques to validate the performance and robustness of AI systems. Additionally, you will collaborate closely with the AI/ML researchers and computational biologists on the team to develop our state-of-the-art AI for biology foundation models.

Requirements

  • M.S. or Ph.D. student (or evidence of equivalent level of expertise) in Computer Science, Artificial Intelligence, Machine Learning, or a related technical field.
  • Skilled in developing, implementing, and debugging deep learning methods/models in popular frameworks, such as JAX, TensorFlow, or PyTorch, with an interest in generative models, graph neural networks, or large-scale deep learning applications.
  • Strong theoretical foundation (e.g., statistics, optimization, graph theory, linear algebra).
  • Passion for interdisciplinary research (emphasizing the intersection of AI and Biology), and willingness to acquire necessary domain knowledge.
  • Motivated and self-driven with the ability to operate with partial descriptions of high-level objectives (as is typical in a start-up environment).
  • Familiarity with software engineering best practices (version control, documentation, etc).

Related Field

  • AI & Machine Learning

Related Subfield

  • AI Research

Languages

  • English

Nice to Haves

  • Proven track record in research and innovation demonstrated through contributions in top-tier AI/ML (e.g., NeurIPS, ICML, CVPR, ECCV, ICCV, ICLR) and/or core biology (e.g., Nature, Science, or Cell) journals and conferences.
  • Intern experience in industry (e.g., OpenAI, FAIR, Deepmind, Google Research).
  • Hands-on experience working at the intersection of AI and Biology.
  • Experience in large-scale distributed training and inference.
  • Open-source contributions, especially if used by others.
▶Apply Now

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