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Biomedical Machine Learning Jobs in New York (NOW HIRING)

Postdoctoral Fellow-MSH

Manhattan, NY · On-site

$53K - $73K/yr

... machine-learning/deep-learning methodology research with application to biomedical data. • Mediation and causal-inference methodology research with application to medical/clinical-trial studies.

Postdoctoral Fellow-MSH

Manhattan, NY · On-site

$53K - $73K/yr

... machine-learning/deep-learning methodology research with application to biomedical data. • Mediation and causal-inference methodology research with application to medical/clinical-trial studies.

To qualify you must have a Masters degree in a quantitative discipline (Biomedical Informatics, Computer Science, Machine Learning, Applied Stascs, Mathematics or similar field) and 3 years of ...

Research Associate

New York, NY · On-site

$26.37/hr

... Department of Biomedical Engineering. New York University (NYU) is one of the top private ... Working on research projects at the intersection of health and machine learning methods, including ...

Principal Data Scientist

New York, NY · On-site

$204K - $267K/yr

You'll work at the intersection of computational biology, machine learning, and drug development ... Aid in the development and training of AI agents to automate and optimize biomedical workflows

Expectations Candidates will be responsible for * developing statistical signal processing, machine learning, and various mathematical algorithms for biomedical engineering applications * conducting ...

Have training in statistical signal processing, machine learning * Be capabile to apply various mathematical algorithms for biomedical engineering applications * Be able to conduct human subject ...

... processing, machine learning, and capability in applying various mathematical algorithms for biomedical engineering applications, and prepared for conducting human subject research including ...

Postdoctoral Fellow-MSH

Manhattan, NY · On-site

$53K - $73K/yr

This Postdoctoral Research Fellowship position will focus primarily on using biomedical data science and machine learning methodologies to explore cardiovascular disease phenotypes in the Mount Sinai ...

Internship Program

New York, NY · On-site

$18.25 - $23.75/hr

Software Engineering, Hardware Engineering, Machine Learning Research, Industrial Design, and UI/UX ... Biomedical Engineering, Neuroscience, Mechanical/Industrial Design, or a related field.

Internship Program

New York, NY

$18.25 - $23.75/hr

Software Engineering, Hardware Engineering, Machine Learning Research, Industrial Design, and UI/UX ... Biomedical Engineering, Neuroscience, Mechanical/Industrial Design, or a related field.

Internship Program

New York, NY

$18.25 - $23.75/hr

Software Engineering, Hardware Engineering, Machine Learning Research, Industrial Design, and UI/UX ... Biomedical Engineering, Neuroscience, Mechanical/Industrial Design, or a related field.

Showing results 41-60

Biomedical Machine Learning information

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How much do biomedical machine learning jobs pay per hour?

As of Aug 10, 2026, the average hourly pay for biomedical machine learning in New York is $31.21, according to ZipRecruiter salary data. Most workers in this role earn between $26.54 and $35.24 per hour, depending on experience, location, and employer.

How to become a biomedical machine learning specialist?

To become a biomedical machine learning specialist, individuals typically need a strong background in computer science, machine learning, and biology, often obtained through a bachelor's or master's degree in related fields. Gaining experience with programming languages like Python or R, and tools such as TensorFlow or PyTorch, is essential, along with understanding biomedical data and clinical applications. Advanced roles may require a Ph.D. or specialized certifications in machine learning or biomedical informatics.

What is a biomedical machine learning?

A Biomedical Machine Learning job involves developing and applying machine learning algorithms to analyze biomedical data for healthcare and research applications. Professionals in this field work with medical imaging, genomics, electronic health records, and wearable device data to improve disease diagnosis, treatment, and patient outcomes. They collaborate with researchers, clinicians, and data scientists to design predictive models and extract insights from complex biological data. This role requires expertise in machine learning, data processing, and domain-specific knowledge in healthcare or life sciences.

What does a biomedical machine learning do?

A typical day in Biomedical Machine Learning involves cleaning and preparing biomedical datasets, developing or refining machine learning models, running experiments, and interpreting results in collaboration with domain experts such as bioinformaticians and clinicians. Professionals often participate in team meetings to discuss project goals, share insights, and adjust research directions based on feedback. The role may also involve reading scientific literature to stay current with new methodologies and contributing to academic publications or technical documentation. Working closely with both technical and healthcare-focused colleagues, you'll help translate data-driven insights into meaningful biomedical solutions that impact patient care or research outcomes.

What are the key skills and qualifications needed to thrive in biomedical machine learning, and why are they important?

To thrive in Biomedical Machine Learning, you need a solid background in statistics, machine learning, programming (Python or R), and a strong understanding of biological or medical data, often supported by advanced degrees in computer science, biomedical engineering, or related fields. Experience with frameworks like TensorFlow, PyTorch, and familiarity with biomedical datasets is highly valued, and certifications in data science or biomedical informatics can be advantageous. Strong analytical thinking, communication skills, and the ability to collaborate with interdisciplinary teams are crucial soft skills. These competencies are vital to developing robust models that address complex healthcare challenges while ensuring scientific rigor and regulatory compliance.

What are the most commonly searched types of Biomedical Machine Learning jobs in New York? The most popular types of Biomedical Machine Learning jobs in New York are:
Infographic showing various Biomedical Machine Learning job openings in New York as of August 2026, with employment types broken down into 1% As Needed, 74% Full Time, 22% Part Time, 1% Temporary, and 2% Contract. Highlights an 88% Physical, 2% Hybrid, and 10% Remote job distribution, with an average salary of $64,912 per year, or $31.2 per hour.

Postdoctoral Fellow-MSH

Mount Sinai Hospital

Manhattan, NY • On-site

$53K - $73K/yr

Full-time

Re-posted 18 days ago


Mount Sinai rating

7.7

Company rating: 7.7 out of 10

Based on 294 frontline employees who took The Breakroom Quiz

158th of 887 rated healthcare providers


Job description


Roles & Responsibilities:
At the Icahn Institute, our vision is to transform biomedical research and healthcare delivery into a data-driven, evidence-based, patient-tailored discipline. The Icahn Institute was founded in 2011 to help advance precision medicine with cutting-edge technologies, novel partnerships between the public and private sectors, and world class computational and analytical resources. By maximally leveraging information from patients around the world, we deliver premier precision care optimized for each patient, while discovering breakthrough, next-generation treatments through insights derived from cutting-edge analytics applied to unprecedented amounts of patient-derived data. We promote a core set of values - designed to promote our future vision of team-oriented, data driven global biomedical research: 1) Do good for the patient, 2) Simplify, 3) Share openly, 4) Focus, 5) Synergize, 6) Contributions, not politics, and 7) Deliver.
What You'll Do:
Postdoc fellows may work on many of the cutting-edge research areas at Mount Sinai, including:
• Analyzing high dimensional molecular profiles including but not constraint to DNA/RNA sequencing, epigenetic, proteomics, and microbiome data;
• Analyzing massive electronic medical record data;
• Analyzing irregular time course data from mobile health studies;
• Scalable machine-learning/deep-learning methodology research with application to biomedical data.
• Mediation and causal-inference methodology research with application to medical/clinical-trial studies.
The ideal candidate will have strong analytical and programming proficiencies and proven expertise in high-dimensional data analysis.
Duties and Responsibilities:
• Develop and use computational techniques to analyze large-scale biomedical datasets.
- Develop and implement proper statistical/computational models;
- Develop and implement proper data visualization tools;
- Perform rigorous and reproducible data analyses;
- Identify and resolve technical issues and propose upgrades to current software;
• Take the lead in manuscripts preparation and facilitate grant writing;
• Collaborate with researches from other disciplines;
• Participate scientific conferences and present research works;
• Other technical and leadership duties as assigned and commensurate with experience and skills
Requirements:
• Ph.D. in Computer Science, Bioinformatics, Statistics, Computational Biology, or other relevant quantitative discipline.
• Good organization and communication skills, with demonstrated ability to productively work as a member of a team.
• Demonstrate outstanding scientific writing skills and experience.
• Experience in data science, machine learning, statistical modeling, genomic analysis, or other relevant analytical field
• Experience in programming environments such as R, Matlab, SAS, Stata, Python/Jupyter
• Working experience with genetics or statistics analysis and online resources or other biomedical data analysis is a plus
About Us
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.

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