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MyOme is seeking a driven Scientist, Computational Biology to join our early-stage research team in the United States. You will leverage large-scale public biobanks to evaluate multi-omic disease risk prediction, spanning observational epidemiology, high-throughput omics, and statistical modeling.
You will work with UK Biobank, All of Us, and multiple omics modalities to discover signatures identifying individuals at risk before clinical onset, collaborating across computational, assay,
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.
Position Overview:
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 You’ll Do:
What You’ll Ne ed:
Education & Experience:
Ph.D. in Computational Biology, Bioinformatics, Biostatistics, Epidemiology, Human Genetics, or a related quantitative field with 0–4 years of experience (or Master’s degree with 3–6 years of relevant experience).
Biobank Expertise: Proven hands‑on experience querying and analyzing multi‑modal data in major human cohorts, specifically UK Biobank and/or All of Us.
Omic Proficiency: Demonstrated experience analyzing at least two of the following human data types:
Plasma proteomics
Metabolomics
Genome-wide DNA methylation (array or sequencing)
Bulk/single‑cell transcriptomics
Epidemiological & Statistical Rigor: Strong background in observational study design, association testing, confounding control, and time‑to‑event modeling on clinical/EHR phenotypes.
Computational Toolkit: High proficiency in Python and/or R, version control (Git), and working in cloud‑based biobank environments (e.g., DNAnexus, Terra, AWS, or GCP).
Statistical Methods & Machine Learning: Well‑versed in statistical approaches applicable to biomarker discovery (e.g., high‑dimensional feature selection, hypothesis testing, regularization) and experienced with standard machine learning workflows (e.g., random forests, gradient boosting, penalized regression); hands‑on experience with deep learning methodologies is preferred.
Preferred / Bonus Qualifications:
Location, Compensation, and Benefits:
San Francisco Bay Area pay range
$130,000—$150,000 USD
Benefits:
Diversity, Inclusion, and Equal Opportunity: MyOme values diversity in all forms. We believe that diverse perspectives drive better science and better patient outcomes. We are an Equal Opportunity Employer committed to creating an inclusive workplace that empowers every individual.
Why Work at MyOme?
Join us if you:
Learn More: myome.com