Postdoctoral Researcher, ML for Biology, Hsu Lab (AI)

Location: Palo Alto, California, United States

Minimum base salary: $80,000 per year. Base salary depends on relevant postdoctoral experience and is not negotiable.

Company

hirify.global is an independent nonprofit research organization working at the interface of artificial intelligence and biology to accelerate scientific progress and understand complex diseases.

What you will do

• Design, execute, and analyze computational experiments in generative AI and computational biology.
• Own an end-to-end research project within the Hsu Lab’s scientific focus, developing increasing independence with guidance from the principal investigator.
• Develop predictive models of life, AI agents and systems, genome-mining approaches, and AI-guided therapeutic discovery methods.
• Publish first-author research, present at national and international conferences, and build collaborations across Arc, Stanford, and the broader Bay Area ecosystem.
• Mentor research associates, technicians, and students while contributing to seminars, symposia, and a collaborative research environment.
• Maintain rigorous coding standards and documentation, contribute to software development, and maintain shared infrastructure.

Requirements

• Ph.D. in Computer Science, Bioinformatics, Computational Biology, Genetics, or Genomics.
• Expertise with Python, bash, and standard deep learning frameworks such as PyTorch.
• Track record of creative, high-impact research demonstrated through publications, patents, tools, or software.
• Excellent written and verbal communication skills.
• Ability to work in a fast-paced environment as an independent thinker and collaborative team member.

Culture & Benefits

• Long-term funding and industry-like research resources without commercial pressure.
• Freedom to pursue high-risk, long-term research projects.
• Collaboration across Arc, Stanford University, UC Berkeley, UC San Francisco, and the broader Bay Area ecosystem.
• Access to platforms for genomics, single-cell technologies, synthetic biology, high-performance computing, and experimental model systems.