The next frontier is authoring new biology, and with AI, we have the power to write the future—creating solutions that transform medicine, agriculture, and beyond. Backed by Insight and Air Street.
About the role
Our generative models learn the blueprint of life by modeling large-scale evolutionary data, enabling us to engineer and write biology in unprecedented ways. We are seeking a passionate Computational Research Intern to join moonshot projects at the intersection of bioinformatics and machine learning. Found on 1752vc Careers, the job board for startup and VC roles.
What they're looking for
- Enrolled in a BS, MS, or PhD program in Bioinformatics, Computational Biology, Computer Science, Statistics, or a related quantitative field
- Strong programming skills in Python and familiarity with scientific computing libraries (e.g., NumPy, pandas, Jupyter)
- Experience in one or more of the following: machine learning, large-scale data analysis, genomics, or protein bioinformatics
- Excellent problem-solving skills, scientific curiosity, and ability to work both independently and collaboratively
More about this role
Profluent is the frontier AI lab for biology. Profluent builds powerful foundation models for all of life's molecules, unlocking solutions that transform medicine, agriculture, and beyond. Founded in 2022 and headquartered in Emeryville, CA, Profluent is backed by leading investors including Altimeter Capital, Bezos Expeditions, Spark Capital, Insight Partners, Air Street Capital, AIX Ventures, and Convergent Ventures and has raised over $150M to date.
Our generative models learn the blueprint of life by modeling large-scale evolutionary data, enabling us to engineer and write biology in unprecedented ways. We are seeking a passionate Computational Research Intern to join moonshot projects at the intersection of bioinformatics and machine learning.
This is a rare opportunity to tackle open-ended scientific and engineering challenges with direct potential for high-impact publications and real-world applications in synthetic biology and protein engineering.
- Design and implement computational approaches to advance cutting-edge research in bioinformatics and machine learning
- Analyze large-scale genomic and protein datasets to uncover new biological insights and capabilities
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