Job description
This is a remote position.
Our Client, a world leader in Biotechnology is looking for a "Computational Scientist - Human Genetics - Remote" for SSF, CAJob Duration: Long Term Contract (Possibility Of Extension)
Pay Rate: $56/hr on W2
Company Benefits:Medical, Paid Sick leave, 401K
The Human Genetics department is seeking a highly independent Computational Scientist with hands-on experience ingenetic epidemiology, statistical genetics, computational biology, or bioinformatics. The role will focus on developing and applying analytical approaches to integrate and interpretgenetic, genomic, and clinical data, including large-scale sequencing and single-cell datasets. The scientist will contribute to multimodal data integration, machine learning, and translational research to generate insights into disease biology.
Key Responsibilities
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.
Required Qualifications
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.
If interested, please send us your updated resume at
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Originally posted on Himalayas
Who can apply
Eligible countries: United States. Accepted UTC offsets: UTC-10, UTC-9, UTC-8, UTC-7, UTC-6, UTC-5, UTC+14. Review the full description for employer-specific work authorization, residency and schedule requirements.