Computational Scientist Human Genetics Remote

This is a remote position.

Job Duration: Long Term Contract (Possibility Of Extension)
Pay Rate: $56/hr on W2

The Human Genetics department is seeking a highly independent Computational Scientist with hands-on experience in genetic epidemiology statistical genetics computational biology or bioinformatics. The role will focus on developing and applying analytical approaches to integrate and interpret genetic 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.

• Analyze large-scale genetic genomic and clinical datasets from 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.
  
• Analyze whole genome sequencing RNA-Seq scRNA-Seq scATAC-Seq and other molecular assay data.
  
• Develop and apply multimodal data integration methods to connect genetic molecular clinical and imaging data.
  
• Implement machine learning algorithms to 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.
  

• PhD or Masters degree with significant relevant experience in Statistical Genetics Computational Biology Bioinformatics Genetic Epidemiology or a related field.
  
• Extensive experience analyzing large-scale genetic/genomic datasets.
  
• Knowledge of genetic epidemiology and statistical genetics.
  
• Experience with GWAS and association analysis using array- or sequence-based human genetic data.
  
• Experience analyzing RNA-Seq single-cell sequencing and/or proteomic data.
  
• Experience integrating genetic and molecular datasets for multimodal analysis.
  
• Strong programming skills in R Python and shell scripting.
  
• Experience with Git and high-performance computing environments such as SLURM.
  
• 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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