Computational Scientist II Single Cell Genomics

Job Duration: Long Term Contract (Possibility Of Extension)

This role is focused on advancing therapeutic discovery through high-content perturbation screening and single-cell genomics. This role will involve analyzing large-scale sequencing datasets developing computational pipelines and collaborating with multidisciplinary teams to generate biological insights that support drug discovery.

• Analyze and interpret large-scale single-cell sequencing datasets (scRNA-seq) generated from high-content perturbation experiments.
  
• Develop and optimize computational workflows for Perturb-seq CROP-seq Sci-Plex and other sequencing-based functional genomics studies.
  
• Apply statistical and computational methods to identify biological mechanisms therapeutic targets and treatment responses.
  
• Collaborate with biologists chemists computational scientists and cross-functional research teams to translate complex data into actionable insights.
  
• Develop reproducible data analysis pipelines using Python and bioinformatics tools.
  
• Perform quality control data integration visualization and statistical analysis of large-scale genomics datasets.
  
• Integrate multimodal datasets including single-cell genomic and clinical data to support research and therapeutic development.
  
• Present findings through scientific reports presentations and collaborations with internal research teams.
  
• Maintain well-documented reproducible computational workflows and contribute to continuous process improvements.
  

• Ph.D. in Computational Biology Bioinformatics Computer Science Statistics Mathematics or a related quantitative life science discipline.
  
• Proven experience analyzing large-scale single-cell RNA sequencing (scRNA-seq) datasets.
  
• Strong programming skills in Python for scientific computing and data analysis.
  
• Solid background in statistics probabilistic modeling and computational data analysis.
  
• Experience working with next-generation sequencing (NGS) and genomics datasets.
  
• Excellent analytical communication and problem-solving skills.
  
• Demonstrated ability to collaborate effectively in multidisciplinary research environments.
  
• Strong publication record demonstrating scientific contributions.
  

• Experience with Perturb-seq CROP-seq Sci-Plex or other CRISPR-based perturbation screening technologies.
  
• Experience with CRISPR functional genomics and single-cell perturbation analysis.
  
• Knowledge of multimodal data integration including genomic transcriptomic and clinical datasets.
  
• Experience using workflow management systems such as Nextflow or Snakemake.
  
• Experience working on High Performance Computing (HPC) environments using SLURM.
  
• Familiarity with cloud computing reproducible workflows and collaborative software development practices.
  

If interested please send us your updated resume at

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