Role overview
PolyCypher Health is a pioneering healthtech and biotech startup focused on decoding complex diseases through the integration of polygenic scoring and health data. The company aims to build precise individualized risk profiles and identify novel genetic drivers of diseases that significantly impact human health. Situated at the intersection of AI, biology, and medicine, PolyCypher is developing an advanced, data-driven technology platform to enhance disease prevention, optimize healthcare, and accelerate the discovery of new therapies. Join us in our mission to revolutionize precision medicine and improve global health outcomes.
*Full Job Description
Research Scientist / Bioinformatics Innovator (Part-Time)**
PolyCypher Health is looking for a postdoc, staff scientist, or student (Bachelor’s, Master’s, or PhD at any stage, given research proficiency) in biostatistics, statistics, computational biology, genomics, applied math, or computer science to help us build the next generation of disease prediction technology. Our mission is to predict diseases before they occur, combining genomics, EHR data, and cutting-edge AI method development.
This is a part-time, flexible contributor role focused on scientific methods, polygenic risk scoring, and model validation. You will also work directly with PolyCypher’s CTO and COO/Lead AI Scientist, influencing core scientific and technical decision-making.
We do not expect candidates to have all skills listed: if you have some of them and a strong desire to learn, you should apply.
What you'll work on
Develop and validate polygenic risk score (PRS) methods.
Test, benchmark, and refine statistical and computational models.
Build and evaluate scientific software within a Python/Rust codebase.
Work with large genomic/EHR datasets supporting research and platform development.
Contribute to open-source scientific tools and internal R&D.
Collaborate asynchronously and independently, making key design decisions.
Work directly with the CTO and COO/Lead AI Scientist on high-impact research and method development.
What we're looking for
Hazard/survival models
Spline models, penalization, or generalized additive modeling
Genomics pipelines, VCF/array data, imputation workflows
Low-level programming (Rust/C/C++)
AI/ML: LLMs, medical language models, agent frameworks, or automation
Software engineering: testing, reproducibility, optimized computation