Location: New York, NY
Cap-Exempt H-1B Position — No lottery required
**Description** We are looking for a Computational Scientist in Computational Biology and Machine Learning to join our growing translational research program at the Tisch Cancer Institute. Our team studies myeloproliferative neoplasms (MPNs), acute myeloid leukemia (AML), and related myeloid malignancies, combining single-cell multi-omics, clinical data, and artificial intelligence–based approaches to understand disease mechanisms, identify biomarkers, support drug development, and improve patient care. The scientist will work closely with longitudinal patient datasets, integrating genomics, immune and cytokine profiling, treatment responses, and clinical trial outcomes. The scientist will report directly to Dr. Md Babu Mia, lead of the Computational Biology and Machine Learning program within the MPN team. **Responsibilities** Computational Biology & Single-Cell Analytics - Lead analysis of single-cell genomics datasets and build reproducible pipelines for data integration, clustering, differential expression, and clonal architecture reconstruction - Apply rigorous statistical methods that appropriately account for sample-level replication, longitudinal structure, and multi-modal data Machine Learning & Predictive Modeling - Build machine learning models linking genomic drivers to clinical phenotypes, cytokine profiles, and treatment outcomes using ensemble methods and deep learning - Develop interpretable risk stratification models for disease progression and treatment response, with a focus on clinical relevance AI & Large Language Model Development - Develop retrieval-augmented generation (RAG) systems and AI-assisted workflows that enable natural-language querying of clinical and genomic datasets - Build LLM-powered pipelines for extracting structured information from clinical notes and pathology reports, with an emphasis on transparency and clinical usability Data Integration & Infrastructure - Build unified data models connecting treatments, laboratory result