Member of Technical Staff - Computational Biology
Edison Scientific, San Francisco, California, United States, 94199
Member of Technical Staff - Computational Biology
About
Edison Scientific focuses on building and commercializing AI agents for science, and shares FutureHouse’s mission to build an AI Scientist - scaling autonomous research, productizing it, and applying it to critical challenges such as drug development.
Role As a Member of Technical Staff - Computational Biology, you'll build and evaluate AI agent systems to automate biological discovery. You'll focus on improving how LLMs execute complex scientific tasks, creating benchmarks to measure their performance, and collaborating with researchers to generate and validate novel findings in biology.
You’ll be working alongside exceptionally smart, mission-driven people on problems that genuinely matter. You’ll be advancing science and making breakthrough discoveries in basic research. We are well-resourced with a wet lab, extensive compute, and the tools you need to do your best work. We publish our findings.
Responsibilities
Improving the ability of LLM agents to execute long, coherent data-driven discovery tasks
Building benchmarks to automatically evaluate the performance of LLM agents on a wide variety of scientific tasks
Working with collaborators to apply AI agents to make novel discoveries in biology
Evaluating the accuracy of AI-generated discoveries through independent human analysis
Leading or contributing to publications describing technical achievement
Requirements
PhD in biological science, broadly defined
Experience analyzing one or more of the following types of complex biological data in a first-author publication: sc-omics data, high throughput screen data, proteomics or lipidomics data, human genetic data, imaging data, or protein structure data.
Expertise in one area of mammalian biology
Familiar with the advantages and limitations of chat-based LLM and agentic coding tools to perform data analysis tasks in biological research
Strong critical thinking skills and ability to identify mistakes in LLM-generated analyses
Excellent written and verbal communication skills
You enjoy quickly iterating on ideas through rapid prototyping
You operate with high independence, and like to execute complex tasks to completion with minimal supervision
You thrive when working on a diversity of projects in sprint-based formats, and have high comfort with uncertainty
You enjoy trying out the newest AI tools
You are proficient in experimental design, and could execute experiments yourself or via a CRO if necessary
Location + Compensation
Collaboration is at the heart of discovery. We work on-site to stay close to the science, move faster as a team, and share the kind of energy that only happens when smart, curious people build together- in a space that we love to be in!
Location:
San Francisco (Dogpatch) Remote U.S. locations will be considered for the right fit.
At Edison Scientific, we know that titles can cover a range of experience levels. Actual base pay will depend on factors such as skills, experience, and scope of responsibility. Compensation ranges may evolve as we continue to grow. In addition to base pay, team members are eligible for equity, benefits, and other perks.
Compensation:
$160,000 - $250,000+ and equity
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Role As a Member of Technical Staff - Computational Biology, you'll build and evaluate AI agent systems to automate biological discovery. You'll focus on improving how LLMs execute complex scientific tasks, creating benchmarks to measure their performance, and collaborating with researchers to generate and validate novel findings in biology.
You’ll be working alongside exceptionally smart, mission-driven people on problems that genuinely matter. You’ll be advancing science and making breakthrough discoveries in basic research. We are well-resourced with a wet lab, extensive compute, and the tools you need to do your best work. We publish our findings.
Responsibilities
Improving the ability of LLM agents to execute long, coherent data-driven discovery tasks
Building benchmarks to automatically evaluate the performance of LLM agents on a wide variety of scientific tasks
Working with collaborators to apply AI agents to make novel discoveries in biology
Evaluating the accuracy of AI-generated discoveries through independent human analysis
Leading or contributing to publications describing technical achievement
Requirements
PhD in biological science, broadly defined
Experience analyzing one or more of the following types of complex biological data in a first-author publication: sc-omics data, high throughput screen data, proteomics or lipidomics data, human genetic data, imaging data, or protein structure data.
Expertise in one area of mammalian biology
Familiar with the advantages and limitations of chat-based LLM and agentic coding tools to perform data analysis tasks in biological research
Strong critical thinking skills and ability to identify mistakes in LLM-generated analyses
Excellent written and verbal communication skills
You enjoy quickly iterating on ideas through rapid prototyping
You operate with high independence, and like to execute complex tasks to completion with minimal supervision
You thrive when working on a diversity of projects in sprint-based formats, and have high comfort with uncertainty
You enjoy trying out the newest AI tools
You are proficient in experimental design, and could execute experiments yourself or via a CRO if necessary
Location + Compensation
Collaboration is at the heart of discovery. We work on-site to stay close to the science, move faster as a team, and share the kind of energy that only happens when smart, curious people build together- in a space that we love to be in!
Location:
San Francisco (Dogpatch) Remote U.S. locations will be considered for the right fit.
At Edison Scientific, we know that titles can cover a range of experience levels. Actual base pay will depend on factors such as skills, experience, and scope of responsibility. Compensation ranges may evolve as we continue to grow. In addition to base pay, team members are eligible for equity, benefits, and other perks.
Compensation:
$160,000 - $250,000+ and equity
#J-18808-Ljbffr