Remote AI Biologist for Rare Disease Research

latch.bio; San Francisco (CA); Remote; USD 140,000 - 180,000; Full time

Benefits offered by this job

Health, dental, vision

PTO: 12 days

401(k)

Job summary

latch.bio is seeking a senior researcher to shape how AI agents assist in diagnosing, treating, and discovering therapies for rare and progressive diseases. You will work with scientists, physicians, software engineers, and computational biologists to build rigorous benchmark datasets and validate analytical steps that mimic expert scientists.

You will help design experiments, contribute to wet/dry lab strategies, and advance methods for target discovery while advancing open science and

Qualifications

• Advanced degree in biology, genetics, physiology, computational biology, or related field.
• 3+ years hands-on research with publishable impact or industry experience.
• Proficiency in Python and/or R for data analysis and visualization.
• Deep scientific or clinical expertise in at least one relevant disease area.

Responsibilities

• Contribute to the technical approach for evaluating AI agents in diagnosis, treatment, and research.
• Collaborate with scientists, physicians, software engineers, and computational biologists.
• Build ground-truth benchmark datasets drawn from studies and original work.
• Test whether agents can perform analytical and interpretative steps of expert scientists.
• Design and troubleshoot experiments in wet or dry lab settings as applicable.

Skills

Biology/Genetics expertise

Data analysis

Python and/or R

Scientific communication

Education

Advanced degree (MS/MD/PhD/PharmD) in biomedical field

Tools

Python

R

Job description

latch.bio is seeking a senior researcher to shape how AI agents assist in diagnosing, treating, and discovering therapies for rare and progressive diseases. You will work with scientists, physicians, software engineers, and computational biologists to build rigorous benchmark datasets and validate analytical steps that mimic expert scientists.

You will help design experiments, contribute to wet/dry lab strategies, and advance methods for target discovery while advancing open science and