D. in Mathematics, Computer Science, Engineering, Bioinformatics, Computational Biology, or a related quantitative field with strong domain knowledge in molecular biology and genomics./liliProficiency in Python (and/or R) for data analysis, statistical modeling, and machine learning in a scientific computing environment./liliHands-on experience with AWS cloud computing platform./lili5+ years of relevant experience applying quantitative, statistical, and computational approaches in biotech, life sciences, or translational research./liliDemonstrated experience in computational biology, including analysis and interpretation of high-throughput biological data such as genomics, transcriptomics, proteomics, epigenomics, or other multi-omics modalities./liliHands-on experience working with molecular, cellular, clinical, and/or multi-omics datasets, including data QC, normalization, integration, and downstream analysis./liliStrong ability to translate biological and clinical research questions into statistically sound and computationally efficient analytical solutions./liliWorking knowledge of bioinformatics tools, pipelines, and data formats (e.g., FASTQ, BAM/CRAM, VCF, GTF, HDF5, or equivalent)./liliProficiency with Linux and command-line workflows commonly used in bioinformatics and computational research./liliExperience querying and working with complex relational and non-relational databases./liliStrong verbal and written communication skills, with the ability to clearly explain complex biological and computational concepts to multidisciplinary audiences./liliTeam-oriented mindset with a passion for personalized medicine, data-driven discovery, and scientific innovation./li/ulpPreferred Qualifications/pulliExperience in cancer biology, molecular biology, biomarker discovery, or diagnostic development./liliProven experience developing and validating predictive models using machine learning, deep learning, LLM and/or Agentic AI techniques./liliExperience designing and maintaining relational (e.g., MySQL, PostgreSQL) and non-relational (e.g., MongoDB) databases./liliExperience developing data-driven or analytics-enabled applications./liliFamiliarity with modern software engineering best practices, including CI/CD, containerization, microservices, and system architecture./liliKnowledge of DevOps, MLOps, and/or DataOps concepts and tooling./liliDemonstrated success working in multidisciplinary, cross-functional teams./li/ulpPhysical