University of Texas Medical Branch-posted 26 days ago
$48,000 - $60,000/Yr
Full-time • Mid Level
Hybrid • Galveston, TX
5,001-10,000 employees
Educational Services

To provide technical skills in the preparation and use of programs for the solution of problems by electronic computers. Join a multidisciplinary team developing next-generation optical imaging systems for neurosurgery. This position will focus on designing and optimizing software to control and integrate optical components (LEDs, cameras, filters, motion systems), while developing robust pipelines for real-time data acquisition, visualization, and analysis. A central objective is to leverage the data generated from these systems to build and train machine learning and AI algorithms for improved image-based detection and classification using advanced image processing techniques. The work directly supports translational technology development-taking innovations from bench to bedside to improve visualization and precision during brain tumor surgery.

  • Develop and maintain Python-based control software for optical subsystems (LED drivers, cameras, filters, motorized stages, DAQs, etc.).
  • Design and implement real-time data acquisition and visualization pipelines for fluorescence, spectral, and photoacoustic imaging.
  • Build and evaluate machine learning models (e.g., classification, segmentation, regression) for improved detection and image analysis.
  • Collaborate with optical engineers, neuroscientists, and clinicians to integrate software with hardware systems and perform benchtop and intraoperative validation.
  • Translate research-grade prototypes into clinically deployable systems
  • Maintain organized documentation, version control (Git), and contribute to shared multi-site data workflows.
  • Associate's degree or equivalent in related field and one year related experience.
  • Bachelor's or Master's degree in Computer Engineering, Computer Science,Electrical Engineering, or related field.
  • Proficiency in Python required; strong experience in libraries such as NumPy,OpenCV, scikit-learn, TensorFlow, or PyTorch.
  • Experience interfacing with optical and electronic components (e.g., cameras,LEDs, filter wheels, motion stages, serial/USB communication).
  • Working knowledge of image processing and signal analysis.
  • Demonstrated ability to design, test, and document engineering systems in a collaborative environment.
  • Experience with real-time image acquisition and GPU acceleration (CUDA orOpenCL).
  • Familiarity with biomedical or scientific imaging systems.
  • Experience with machine learning or AI-driven image analysis.
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