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Position Summary:

We have an exciting opportunity to join our team as a Research Engineer.

 The research engineer will develop and maintain computational tools and analysis pipelines for advanced MRI research, with a focus on quantitative diffusion MRI and large-scale neuroimaging datasets. Responsibilities include developing reliable software workflows, improving reproducibility of imaging analysis pipelines, and contributing to machine learning methods for MRI data analysis.
The position involves close collaboration with Principal Investigators, physicists, and data scientists, while working independently within the scientific framework of the laboratory.

Job Responsibilities:

As part of the project team, the research engineer will be involved in the following activities:

Develop and maintain software tools and analysis pipelines for MRI data processing.

Optimize existing code and develop new computational modules.

Implement software engineering best practices, including testing and version control.

Support reproducible and containerized computational workflows.

Contribute to development of machine learning models for neuroimaging applications.

Work collaboratively with engineers, physicists, and neuroscientists.

Perform code maintenance, documentation, and testing.

Contribute to research projects, scientific manuscripts, and conference presentations.

Provide technical guidance to students and postdoctoral fellows.

Minimum Qualifications:
To qualify you must have a BS.

Preferred Qualifications:
MS degree in computer science, data science, biomedical engineering, or related discipline
and 13 years of experience, or an equivalent combination of education and experience.
Strong programming skills in Python and experience with scientific computing.
Familiarity with machine learning methods.
Experience with software development tools such as Git and automated testing.
Experience with large-scale data processing and containerized workflows is preferred.
Familiarity with medical imaging or neuroimaging analysis is desirable.

Qualified candidates must be able to effectively communicate with all levels of the organization.

NYU Grossman School of Medicine provides its staff with far more than just a place to work. Rather, we are an institution you can be proud of, an institution where you'll feel good about devoting your time and your talents. At NYU Langone Health, we are committed to supporting our workforce and their loved ones with a comprehensive benefits and wellness package. Our offerings provide a robust support system for any stage of life, whether it's developing your career, starting a family, or saving for retirement. The support employees receive goes beyond a standard benefit offering, where employees have access to financial security benefits, a generous time-off program and employee resources groups for peer support. Additionally, all employees have access to our holistic employee wellness program, which focuses on seven key areas of well-being: physical, mental, nutritional, sleep, social, financial, and preventive care. The benefits and wellness package is designed to allow you to focus on what truly matters. Join us and experience the extensive resources and services designed to enhance your overall quality of life for you and your family.

NYU Grossman School of Medicine is an equal opportunity employer and committed to inclusion in all aspects of recruiting and employment. All qualified individuals are encouraged to apply and will receive consideration. We require applications to be completed online.

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NYU Langone Health provides a salary range to comply with the New York state Law on Salary Transparency in Job Advertisements. The salary range for the role is $84,577.92 - $90,000.00 Annually. Actual salaries depend on a variety of factors, including experience, specialty, education, and hospital need. The salary range or contractual rate listed does not include bonuses/incentive, differential pay or other forms of compensation or benefits.

To view the Pay Transparency Notice, please click here