Research Assistant Professor - Software Engineering

The University of Texas at El Paso; El Paso (TX); On-site; USD 80,000 - 100,000; Full time

Benefits offered by this job

Excellent fringe benefits

Job summary

The University of Texas at El Paso is seeking a non-tenure-track Research Assistant Professor in Software Engineering to lead software development for a brain mapping project. Candidates should have a Ph.D. or a Master's degree with relevant experience. The role involves mentoring, adopting software practices like Agile, and collaborating across disciplines.

Salary is commensurate with experience, and the position is renewable for a maximum of three years depending on funding and performance. UTEP values a diverse and inclusive environment.

Qualifications

• Ph.D. in computer science, software engineering, biomedical informatics, or related field.
• Experience with Agile project management and software development best practices.
• Proficiency in Python and another language relevant to scientific computing.

Responsibilities

• Lead software engineering practices for the research software development.
• Develop the rat-to-atlas mapping pipeline components.
• Collaborate on software requirements with interdisciplinary teams.

Skills

Agile project management

Mentoring

Python

Software engineering practices

Interdisciplinary teamwork

Education

Ph.D. in relevant field

Master's degree with research experience

Tools

Docker

Python-based community tooling

Job description

Location: El Paso, TX Category: Science Job Type: Full-time Posted On: Wed May 27 2026

Job Description

The Department of Biological Sciences at The University of Texas at El Paso (UTEP) is hiring a non-tenure-track Research Assistant Professor in Software Engineering. The position is one of four in a coordinated cluster hire - joining colleagues in behavioral neuroscience, brain circuit imaging and atlas mapping, and machine learning and AI - that will expand a cross-college team studying the brain circuits underlying craving, reward, and addiction. The hire will lead software development for an integrated rat-to-atlas brain mapping pipeline and its atlas infrastructure: the open-access atlas Brain Maps 4.0 and the recently released Chemopleth 1.0 spatial database. The role pairs naturally with UTEP's Master of Science in Software Engineering program, offering opportunities to mentor graduate student teams, draw practicum projects from the cluster's atlas work, and engage with the program's professional curriculum. The position also carries a distinctive responsibility in the current moment: as AI-assisted development matures, the engineer at the center of this project will supply the human judgment and anatomical-domain expertise that a production-grade brain atlas platform needs – using modern AI tools where they accelerate the work, and pushing back, with rigor, on outputs that compromise spatial accuracy, anatomical interpretability, or release readiness.

Position Responsibilities

• Lead the adoption of software engineering best practices for the cluster's research software development, including Agile project management (e.g., Scrum or Kanban), code review, automated testing, continuous integration, and release management.
• Architect and develop software components of the rat-to-atlas mapping pipeline, including data ingestion, processing, and visualization tools.
• Develop the Brain Maps 4.0 and Chemopleth 1.0 software toward robust public releases, building on existing prototypes with latitude to refactor or rebuild as engineering judgment requires, and ensuring interoperability with international neuroinformatics infrastructure such as EBRAINS and with Python-based community tooling such as the BrainGlobe Atlas API.
• Collaborate with cluster-hire colleagues in behavioral neuroscience, circuit imaging and mapping, and ML/AI to translate research requirements into reliable software and to support multi-modal data integration and atlas development.
• Contribute to peer-reviewed publications and federal grant applications describing the cluster's software, data, and infrastructure outputs, including the open-access digital atlas of brain reward circuits.
• Mentor graduate and undergraduate trainees to contribute their efforts to the research pipeline.

Job Requirements

• Ph.D. in computer science, software engineering, biomedical informatics, computational science, or a related field; or a Master's degree with substantial professional research software engineering experience.
• Experience with software engineering best practices, including Agile project management (e.g., Scrum or Kanban), version control, automated testing, code review, and documentation.
• Demonstrated experience designing and shipping non-trivial scientific or research software, evidenced by repositories, releases, or production deployments.
• Proficiency in Python and at least one additional language relevant to scientific computing or web infrastructure.
• Experience mentoring or training undergraduate or graduate students in software engineering practice, including supervision of student software projects.
• Demonstrated interest in or experience with neuroscience, biomedical imaging, or related scientific domains.
• Demonstrated ability to work in interdisciplinary teams that translate scientific and experimental requirements into reliable software.

Preferred Qualifications

• Experience working in academic or research-intensive environments, including open-source scientific projects
• Familiarity with neuroscience or biomedical data formats and standards
• Track record of independent grant submissions or co-authored funded proposals related to research software, infrastructure, or scientific computing.
• Experience with web-based scientific applications, data visualization, or large-image rendering
• Experience with containerization (e.g., Docker) and cloud or HPC deployment of scientific software.
• Engagement with FAIR data principles and shared neuroscience infrastructure (e.g., EBRAINS, NIH BRAIN Initiative resources)

Additional Information

Appointment: Non-tenure-track Research Assistant Professor. Initial appointment is for 12 months, renewable contingent on performance and funding availability. The position can be renewed for a maximum of 3 years; renewal beyond 3 years will depend on the candidate's ability to secure extramural funding.

Salary: Commensurate with experience and qualifications. The salary will depend on the candidate's qualifications and experience and includes excellent fringe benefits. Hiring decisions are based on budget approval.

In keeping with its access, excellence, and impact mission, The University of Texas at El Paso is committed to an open, diverse, and inclusive learning and working environment that honors the talents, respects the differences, and nurtures the growth and development of all. We seek to attract faculty and staff who share our commitment.

The University of Texas at El Paso is an Equal Opportunity Employer. The University does not discriminate on the basis of race, color, national origin, sex, religion, age, disability, genetic information, veteran status, or sexual orientation and gender in employment or the provision of services in accordance with state and federal law. Discrimination on the basis of sex includes an employee's or prospective employee's right to be free from sexual harassment under Title IX of the Higher Education Amendments of 1972. Inquiries—includ ing the filing of a Formal Complaint or reporting an incident—about the application of Title IX may be referred to the Title IX Coordinator, who can be reached by phone at [phone], by email at [e-mail], or by mail at 500 W. University Ave., El Paso, TX, Kelly Hall, Room 312.

For accommodation information for employees and applicants with disabilities, please contact UTEP's Equal Opportunity Office at [e-mail].

To the extent that this position involves research, work, or access to critical infrastructure as referenced in Executive Order GA-48, being hired for and continuing to be employed in this position requires the ability to maintain the security or integrity of the infrastructure.