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How much do neuroimaging data analyst jobs pay per year?

As of Aug 22, 2026, the average yearly pay for neuroimaging data analyst in Texas is $76,992.00, according to ZipRecruiter salary data. Most workers in this role earn between $58,200.00 and $90,400.00 per year, depending on experience, location, and employer.

What is a neuroimaging data analyst?

A Neuroimaging Data Analyst processes, analyzes, and interprets brain imaging data from techniques like MRI, fMRI, and PET. They develop and apply computational methods to extract meaningful insights from neuroimaging studies, often working with neuroscientists, clinicians, and researchers. Their role involves scripting, statistical analysis, and data visualization to support research on brain function, structure, and disorders. Proficiency in programming languages like Python, MATLAB, or R, as well as experience with neuroimaging software (e.g., FSL, SPM, AFNI), is typically required.

What does a neuroimaging data analyst do?

A typical day for a Neuroimaging Data Analyst involves preprocessing raw neuroimaging data, running analyses using specialized software, and collaborating with researchers to interpret and visualize results. You might spend part of your day writing scripts, troubleshooting data quality issues, or attending meetings to discuss research project goals and timelines. The role often includes maintaining detailed documentation of data workflows and ensuring all processes align with established scientific and ethical standards. Regular interaction with neuroscientists, clinicians, and other data specialists is common, making teamwork and communication vital aspects of daily work.

What are the key skills and qualifications needed to thrive as a neuroimaging data analyst?

To thrive as a Neuroimaging Data Analyst, you need a solid background in neuroscience, statistics, and data science, often supported by a relevant degree in neuroscience, biomedical engineering, or a related field. Expertise with neuroimaging software (such as SPM, FSL, or AFNI), programming languages like Python or MATLAB, and familiarity with MRI, fMRI, or PET data formats are typically required. Excellent problem-solving skills, attention to detail, and the ability to communicate complex findings clearly are valuable soft skills for this role. These competencies are essential for accurately processing and interpreting neuroimaging data, supporting impactful research, and facilitating collaboration within multidisciplinary research teams.

What are the most commonly searched types of Neuroimaging Data Analyst jobs in Texas?

The most popular types of Neuroimaging Data Analyst jobs in Texas are:

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For Neuroimaging Data Analyst jobs in Texas, the most frequently searched job titles are:

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Neuroimaging Data Analyst jobs near you
Infographic showing various Neuroimaging Data Analyst job openings in Texas as of August 2026, with employment types broken down into 88% Full Time, and 12% Part Time. Highlights an 95% In-person, and 5% Remote job distribution, with an average salary of $76,992 per year, or $37 per hour.

ASSISTANT PROFESSOR - Advanced Imaging (Neuroimaging) [Req#: 882134, Position#: 126668]

UT Southwestern Medical Center

Dallas, TX • On-site

Full-time

Re-posted 22 days ago

UT Southwestern rating

7.9

Company rating: 7.9 out of 10

Based on 152 frontline employees who took The Breakroom Quiz

107th of 891 rated healthcare providers

Job description

Description
The Advanced Imaging Research Center (AIRC) at UT Southwestern Medical Center in Dallas, Texas, invites applications for a tenure-track Assistant Professor position in the field of methodological development for neuroimaging.
Potential topics include but are not limited to the development of innovative neuroimaging data analysis methods for human and pre-clinical applications and / or human 3T and 7T neuroimaging data acquisition methods. Research areas of interest include (i) functional MRI (i.e. Ultra-High resolution/layer specific, networks, novel analysis algorithms, distortion free acquisition); (ii) diffusion weighted MRI (i.e. Advanced modeling, model validation, spinal cord/heart); (iii) susceptibility weighted (SWI), quantitative (t1/t2/mt) and anatomical (Morphometry) MRI (i.e. Processing and quantification, motion correction, parallel transmission); (iv) functional and quantitative perfusion and angiography MRI and (v) machine-learning based reconstruction and analysis approaches. Integration of Neuro MRI with complementary functional neuroimaging methods such as simultaneous EEG or PET or cross-validation against invasive methods to enhance the physiological interpretation of neuroimaging contrasts is also a topic of great interest.
Qualifications
Applicants for this position should have a strong scientific record of accomplishment in neuroimaging methods development including novel data analysis and/or acquisition approaches and/or innovative approaches to validate neuroimaging contrasts supported by respective publications and grants. Experience in supervising graduate students and/or postdoctoral researchers is preferred. Applicants should have a Ph.D. degree in electrical engineering, physics, computational science, biomedical engineering or applied mathematics. Experience in either the development of novel and comprehensive data analysis pipelines or MRI sequence development is required. Faculty are expected to develop an independent, externally-funded research program and actively engage with clinical and basic research faculty across campus to apply the latest neuroimaging technologies to probe human brain function in health and diseases.
Application Instructions
Applications should include a letter of interest and a curriculum vitae.

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