Backed by Sequoia.
About the role
We are seeking a driven, analytical Scientist, Computational Biology to join our early-stage research team. In this role, you will leverage large-scale, publicly available human biobanks to evaluate the feasibility of multi-omic disease risk prediction. You will sit at the intersection of observational epidemiology, high-throughput omics, and statistical modeling. You will mine rich human datasets to discover, evaluate, and validate multi-omic signatures that identify individuals at risk before clinical onset.
What they're looking for
- Experience constructing integrated multi-omic risk scores or combining omics with Polygenic Risk Scores (PRS)
- Familiarity with causal inference methods (e.g., Mendelian Randomization)
- Experience working in an agile, early-stage biotech startup environment
More about this role
MyOme’s mission is to provide clinically actionable genetic information to patients throughout their lives. We combine clinical-grade whole genome sequencing, advanced AI methods for genome interpretation, and seamless digital tools for doctors and patients to order and access results. Our team is composed of seasoned entrepreneurs, scientists, and operators, and we're backed by top-tier investors.
We are seeking a driven, analytical Scientist, Computational Biology to join our early-stage research team. In this role, you will leverage large-scale, publicly available human biobanks to evaluate the feasibility of multi-omic disease risk prediction. You will sit at the intersection of observational epidemiology, high-throughput omics, and statistical modeling. You will mine rich human datasets to discover, evaluate, and validate multi-omic signatures that identify individuals at risk before clinical onset.
- Biobank Data Mining: Ingest, process, and perform quality control on large-scale public human datasets, with an emphasis on the UK Biobank and the All of Us Research Program .
- Multi-Omics Analysis: Analyze complex human molecular profiling data, drawing from modalities such as...
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