Computational Biologist

Rudiment Labs is seeking a talented Computational Biologist to join our Genomics & Bioinformatics team. In this role, you will analyze complex genomic data to identify biomarkers and develop predictive models for cancer progression, working at the intersection of biology, data science, and oncology.

As a Computational Biologist at Rudiment, you will be at the forefront of cancer genomics research, applying computational methods to analyze large-scale biological datasets and extract meaningful insights. You'll work closely with our multidisciplinary team to develop and implement novel algorithms that can identify biomarkers, predict disease progression, and inform personalized treatment strategies.

You'll leverage your expertise in computational biology, statistics, and machine learning to tackle complex biological questions and contribute to our mission of transforming cancer research and care. Your work will directly impact our understanding of cancer biology and potentially lead to new diagnostic tools and therapeutic approaches.

• Analyze high-dimensional genomic data including single-cell RNA-seq, whole-genome sequencing, methylation, and proteomics datasets
• Develop computational methods to identify cancer biomarkers and molecular signatures associated with disease progression and treatment response
• Build and validate predictive models of cancer progression using machine learning approaches
• Integrate multi-omics data to gain comprehensive insights into cancer biology
• Collaborate with wet lab scientists to design experiments and validate computational findings
• Develop and maintain computational pipelines and data processing workflows
• Publish research findings in peer-reviewed journals and present at scientific conferences
• Stay current with the latest developments in computational biology and cancer genomics

• PhD in Computational Biology, Bioinformatics, Genomics, or a related field
• 3+ years of experience analyzing high-throughput genomic data
• Strong programming skills in R, Python, or other languages relevant to bioinformatics
• Experience with machine learning approaches for biological data analysis
• Demonstrated track record of analyzing genomic data including RNA-seq, DNA-seq, or other high-throughput sequencing data
• Strong statistical background and experience with relevant bioinformatics tools and databases
• Strong publication record in computational biology or related fields

• Experience with single-cell sequencing data analysis
• Knowledge of cancer biology and prior experience in cancer genomics research
• Experience with multi-omics data integration
• Familiarity with cloud computing platforms (e.g., AWS, GCP) for large-scale data analysis
• Experience with containerization (Docker, Singularity) and workflow management systems (Nextflow, Snakemake)
• Experience with database design and management for biological data

Ready to join us in our mission to transform cancer research? Submit your application below.

Please note that we review all applications carefully and will contact selected candidates for interviews.

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