The research engineer at Vanderbilt University, particularly within the Biomedical Image Analysis for
Image Guided Interventions Laboratory (BAGL), will likely be involved in supporting faculty, staff, and
students in high-impact research by developing and optimizing software solutions. This involves
designing, developing, and maintaining software systems, evaluating and testing new software,
optimizing software for performance and writing and testing code.

NOTE: A Term position is a staff position that exists for a period longer than six months but is not expected to last beyond one year. Although a position may exist for a specified or indefinite period, staff who accept term positions are not guaranteed employment for the entire period; they are employed for indefinite periods within the limit of the appointment. There are no guarantees of continued employment, either within the term or when the term ends.

Key Functions and Expected Performance:

Designing, developing, and maintaining software systems
Optimizing software systems for speed and scalability
Writing and testing code
Operating data collection software that will interface with hardware systems
Using intra-operative software to support augmented reality-guided surgery research
Maintaining existing and designing new database systems and web-based data visualization and analysis interfaces
Supervisory Relationships: This position does not have supervisory responsibility. This position reports administratively and functionally to the Principal Investigator.

Qualifications

A Bachelor of Science or Bachelor of Engineering degree from an accredited institution or a Master of Science degree in Electrical and Computer Engineering, Computer Science, or other closely related field, is required.

Expertise with Python, Oracle, SQL, and web development is required.
Excellent communication and collaboration skills for working with researchers and other team members are required.
The ability to analyze complex problems and develop effective solutions is required.
Experience with GPU-accelerated computing and data-intensive research preferred.