Computational Biologist (Remote)
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Key skills for this role
About the Role
We are hiring a Computational Biologist to analyze genomic data, interpret biological significance, and develop computational models for precision medicine applications. The role involves processing large-scale sequencing datasets to identify biomarkers and therapeutic targets.
Key Skills for This Role
Responsibilities
- Process and analyze next generation sequencing (NGS) data, including WGS, WES, and RNA Seq, using standardized bioinformatics pipelines
- Interpret genomic variants and their implications for disease mechanisms, drug responses, or patient stratification
- Develop and validate machine learning models to predict clinical outcomes from genomic and phenotypic data
- Generate reproducible research outputs, including reports, visualizations, and statistical summaries for stakeholders
- Stay current with emerging computational biology tools and genomic databases to enhance analytical methodologies
Requirements
- Proficiency in programming languages such as Python or R for genomic data analysis and statistical modeling
- Experience with bioinformatics tools (e.g., GATK, BWA, STAR, DESeq2) and databases (e.g., ClinVar, TCGA, gnomAD)
- Knowledge of machine learning frameworks (e.g., TensorFlow, PyTorch) applied to biological datasets
- Familiarity with cloud computing platforms (e.g., AWS, GCP) for scalable genomic data processing
- Strong background in computational biology, genomics, or a related quantitative field (e.g., bioinformatics, systems biology)
Full Job Posting
Role Overview
- We are hiring for one of our clients seeking a Computational Biology & Genomics Analyst to analyze genomic data, interpret biological significance, and develop computational models for precision medicine applications.
- The role involves processing large scale sequencing datasets to identify biomarkers and therapeutic targets while collaborating with cross functional teams to translate findings into actionable insights.
Key Responsibilities
- Process and analyze next generation sequencing (NGS) data, including WGS, WES, and RNA Seq, using standardized bioinformatics pipelines.
- Interpret genomic variants and their implications for disease mechanisms, drug responses, or patient stratification.
- Develop and validate machine learning models to predict clinical outcomes from genomic and phenotypic data.
- Generate reproducible research outputs, including reports, visualizations, and statistical summaries for stakeholders.
- Stay current with emerging computational biology tools and genomic databases to enhance analytical methodologies.
Required Skills & Qualifications
- Proficiency in programming languages such as Python or R for genomic data analysis and statistical modeling.
- Experience with bioinformatics tools (e.g., GATK, BWA, STAR, DESeq2) and databases (e.g., ClinVar, TCGA, gnomAD).
- Knowledge of machine learning frameworks (e.g., TensorFlow, PyTorch) applied to biological datasets.
- Familiarity with cloud computing platforms (e.g., AWS, GCP) for scalable genomic data processing.
- Strong background in computational biology, genomics, or a related quantitative field (e.g., bioinformatics, systems biology).
More About the Opportunity
- This role offers the chance to contribute to groundbreaking research in precision medicine, leveraging advanced computational techniques to impact patient care globally.
- The contract includes access to high performance computing resources and collaboration with domain experts in genomics and clinical research.
Equal Opportunity Employer
- We hire based on skills and expertise.
- All qualified candidates are welcome regardless of background, experience, or prior employment history.
- Applications are reviewed solely on demonstrated technical ability and qualifications.
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