Website Katalyst Healthcares & Life Sciences
Katalyst Healthcares & Life Sciences
Company : Katalyst Healthcares & Life Sciences
Responsibilities:
Design and implement bioinformatics pipelines for NGS data analysis (e.g., RNAseq, WES, CRISPR screens).
Develop and apply statistical models and machine learning algorithms to analyze multi-modal datasets.
Integrate and interpret genomic, transcriptomic, and other biological data to uncover Client insights into cancer biology and therapeutic targets.
Collaborate with oncology project teams to address scientific questions and deliver impactful results.
Create high-quality visualizations (e.g., ggplot2, Plotly) and interactive dashboards (e.g., RShiny) to communicate complex data effectively.
Leverage HPC clusters, cloud computing platforms, and containerization tools (e.g., Docker) for scalable data analysis.
Maintain reproducible workflows using version control systems (e.g., GitHub) and scripting (e.g., shell).
Contribute to publications and presentations showcasing Client methodologies and research findings.
Requirements:
Ph.D. in Bioinformatics, Computational Biology, Statistics, Mathematics, Computer Science, Genomics, Cancer Biology, Immunology, or a related field.
Master’s degree with 3–5 years of relevant experience, or Bachelor’s degree with 6–8 years of experience in bioinformatics or oncology research.
Expertise in NGS data analysis, including RNAseq, WES, and CRISPR screens.
Proficiency in R and Python programming for statistical modeling and bioinformatics applications.
Experience with HPC environments, cloud platforms, and containerization tools like Docker or Apptainers.
Advanced data visualization skills using tools like ggplot2, Plotly, and RShiny for dashboard development.
Solid understanding of oncology, including cancer biology, tumor dependencies, and signaling pathways.
Strong track record of research publications in oncology and bioinformatics.
Knowledge of predictive modeling, machine learning, and statistical analysis methods.
Excellent written and verbal communication skills to present data insights to diverse audiences.
Familiarity with version control systems (e.g., GitHub) and shell scripting.
Experience in developing bioinformatics tools and workflows for clinical development projects.