Trainee Computational Scientist Jobs (NOW HIRING)

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.

Strength through Unity and Inclusion

The Mount Sinai Health System is committed to fostering an environment where everyone can contribute to excellence. We share a common dedication to delivering outstanding patient care. When you join us, you become part of Mount Sinai's unparalleled legacy of achievement, education, and innovation as we work together to transform healthcare. We encourage all team members to actively participate in creating a culture that ensures fair access to opportunities, promotes inclusive practices, and supports the success of every individual.

At Mount Sinai, our leaders are committed to fostering a workplace where all employees feel valued, respected, and empowered to grow. We strive to create an environment where collaboration, fairness, and continuous learning drive positive change, improving the well-being of our staff, patients, and organization. Our leaders are expected to challenge outdated practices, promote a culture of respect, and work toward meaningful improvements that enhance patient care and workplace experiences. We are dedicated to building a supportive and welcoming environment where everyone has the opportunity to thrive and advance professionally. Explore this opportunity and be part of the next chapter in our history.

About the Mount Sinai Health System:

Mount Sinai Health System is one of the largest academic medical systems in the New York metro area, with more than 48,000 employees working across eight hospitals, more than 400 outpatient practices, more than 300 labs, a school of nursing, and a leading school of medicine and graduate education. Mount Sinai advances health for all people, everywhere, by taking on the most complex health care challenges of our time - discovering and applying new scientific learning and knowledge; developing safer, more effective treatments; educating the next generation of medical leaders and innovators; and supporting local communities by delivering high-quality care to all who need it. Through the integration of its hospitals, labs, and schools, Mount Sinai offers comprehensive health care solutions from birth through geriatrics, leveraging innovative approaches such as artificial intelligence and informatics while keeping patients' medical and emotional needs at the center of all treatment. The Health System includes more than 9,000 primary and specialty care physicians; 13 joint-venture outpatient surgery centers throughout the five boroughs of New York City, Westchester, Long Island, and Florida; and more than 30 affiliated community health centers. We are consistently ranked by U.S. News & World Report's Best Hospitals, receiving high "Honor Roll" status, and are highly ranked: No. 1 in Geriatrics, top 5 in Cardiology/Heart Surgery, and top 20 in Diabetes/Endocrinology, Gastroenterology/GI Surgery, Neurology/Neurosurgery, Orthopedics, Pulmonology/Lung Surgery, Rehabilitation, and Urology. New York Eye and Ear Infirmary of Mount Sinai is ranked No. 12 in Ophthalmology. U.S. News & World Report's "Best Children's Hospitals" ranks Mount Sinai Kravis Children's Hospital among the country's best in several pediatric specialties. The Icahn School of Medicine at Mount Sinai is ranked No. 11 nationwide in National Institutes of Health funding and in the 99th percentile in research dollars per investigator according to the Association of American Medical Colleges. Newsweek's "The World's Best Smart Hospitals" ranks The Mount Sinai Hospital as No. 1 in New York and in the top five globally, and Mount Sinai Morningside in the top 20 globally.

Equal Opportunity Employer

The Mount Sinai Health System is an equal opportunity employer, complying with all applicable federal civil rights laws. We do not discriminate, exclude, or treat individuals differently based on race, color, national origin, age, religion, disability, sex, sexual orientation, gender, veteran status, or any other characteristic protected by law. We are deeply committed to fostering an environment where all faculty, staff, students, trainees, patients, visitors, and the communities we serve feel respected and supported. Our goal is to create a healthcare and learning institution that actively works to remove barriers, address challenges, and promote fairness in all aspects of our organization.

• Masters degree or equivalent in a domain science; Ph.D in Computational Biology, Bioinformatics, Computer Science, Data Science, or related scientific domain preferred.
• 3 years, preferably in a scientific/academic computing environment or equivalent experience.
• Experience in batch HPC cluster environment with a parallel file system
• Experience installing and supporting bio and chemistry codes (NAMD, AMBER, Matlab, Gromacs, DESMOND) and laboratory equipment such as sequencers, etc.
• Experience with MPI, Open MP and numerical libraries
• Experience with scientific workflows
• Experience with instrumenting and optimizing application codes
• Experience in an academic or research community environment
• Programming experience in any applicable language

Preferred:

• Strong experience with next-generation sequencing data analysis, and proficiency in Python and R
• Demonstrated track record building machine learning models for biomedical applications; familiarity with LLM frameworks or RAG systems
• Experience with cloud or HPC environments, containerization (Docker), and database design
• Background in building dashboards, LLM fine-tuning, and working across laboratory, clinical, and computational teams

• Masters degree or equivalent in a domain science; Ph.D in Computational Biology, Bioinformatics, Computer Science, Data Science, or related scientific domain preferred.
• 3 years, preferably in a scientific/academic computing environment or equivalent experience.
• Experience in batch HPC cluster environment with a parallel file system
• Experience installing and supporting bio and chemistry codes (NAMD, AMBER, Matlab, Gromacs, DESMOND) and laboratory equipment such as sequencers, etc.
• Experience with MPI, Open MP and numerical libraries
• Experience with scientific workflows
• Experience with instrumenting and optimizing application codes
• Experience in an academic or research community environment
• Programming experience in any applicable language

Preferred:

• Strong experience with next-generation sequencing data analysis, and proficiency in Python and R
• Demonstrated track record building machine learning models for biomedical applications; familiarity with LLM frameworks or RAG systems
• Experience with cloud or HPC environments, containerization (Docker), and database design
• Background in building dashboards, LLM fine-tuning, and working across laboratory, clinical, and computational teams
  

Compensation Statement

The Mount Sinai Health System (MSHS) provides salary ranges that comply with the New York City Law on Salary Transparency in Job Advertisements. The salary range for the role is $96,461.00 - $165,465.29 Annually.Actual salaries depend on a variety of factors, including experience, education, and operational need. The salary range or contractual rate listed does not include bonuses/incentive, differential pay or other forms of compensation or benefits.

, 031 - Hematology & Medical Oncology - ISM, Icahn School of Medicine

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 results, cytokines, multi-omic biomarkers, and clinical trial endpoints
• Maintain HIPAA-compliant databases and ETL pipelines, and develop dashboards and APIs to support cross-institutional collaboration
   

Scientific Communication

• Prepare publication-ready figures and analyses, and contribute to manuscripts, grant applications, and research proposals
• Present findings at conferences and collaborate closely with lab scientists and clinicians