PhD, or Master's degree with significant relevant experience, inStatistical Genetics, Computational Biology, Bioinformatics, Genetic Epidemiology, or a related field.
Extensive experience analyzing large-scale genetic/genomic datasets.
Knowledge ofgenetic epidemiology and statistical genetics.
Experience withGWAS and association analysisusing array- or sequence-based human genetic data.
Experience analyzingRNA-Seq, single-cell sequencing, and/or proteomic data.
Experience integrating genetic and molecular datasets formultimodal analysis.
Strong programming skills inR, Python, and shell scripting.
Experience withGitand high-performance computing environments such asSLURM.
C++ experience is a plus.
Ability to work independently, make sound analytical decisions, meet deadlines, and produce high-quality results with minimal supervision.

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Originally posted on Himalayas

Analyze large-scalegenetic, genomic, and clinical datasetsfrom internal studies, clinical trials, high-throughput screens, academic collaborations, industry partners, and public datasets.
Develop computational and statistical approaches to integrate and interpret complex biological datasets.
Analyzewhole genome sequencing, RNA-Seq, scRNA-Seq, scATAC-Seq, and other molecular assay data.
Develop and applymultimodal data integrationmethods to connect genetic, molecular, clinical, and imaging data.
Implementmachine learning algorithmsto identify associations between imaging and omics datasets.
Coordinate the intake, preparation, quality control, and organization of new datasets.
Document analytical workflows, code, methods, findings, and results.
Present scientific findings to Human Genetics teams and cross-functional collaborators.
Contribute to scientific publications and translational research initiatives.

Computational Scientist - Human Genetics - Remote

Summary