COMPUTER SCIENTIST - ENGINEER - RESEARCH ENGINEER - MEDICAL AI

at  Southwest Research Institute

The Intelligent Systems Division develops automated solutions for commercial and government clients in multiple domains including transportation (traffic management, connected automated vehicle), manufacturing robotics, medical prognostics, etc.

REQUIREMENTS:

• Requires a Bachelors or a Masters with a 3.25 GPA in Computer Engineering, Computer Science, Electrical Engineering or directly related
• Coursework and project work related to artificial intelligence/machine learning/computer vision/data mining/Math/Statistics or related with strong emphasis on AI and ML
• 0-5 years: Must have course work in AI and Machine Learning
• Program must have strong programming curriculum related to AI and ML
• Projects or internships related to healthcare AI are beneficial; must have interest in applying AI to the healthcare industry
• A valid/clear driver’s license is required

SPECIAL REQUIREMENTS:

Applicant selected will be subject to a government security investigation and must meet eligibility requirements for access to classified information. Applicant must be a U.S. citizen.

OBJECTIVES OF THIS ROLE:

• Support ongoing research and development projects to improve accuracy and efficiency when diagnosing diseases and develop complex bioinformatics data analysis.
• We work with industry partners to innovate in the area of computational biomedicine.
• Identify and capture new applications for the capabilities you and the team create.
• Additional information about the type of work conducted by the Performance Metrology Group can be found at:
• https://www.swri.org/industries/computational-biomedicine
• https://www.swri.org/industries/bioinformatics-data-analysis-services

DAILY AND MONTHLY RESPONSIBILITIES:

• Develop hardware and/or software solutions for existing and next-generation healthcare applications.
• Interact constantly with technical clients and colleagues to understand requirements and constraints of the task objectives.
• Work in various phases of the system lifecycle, including applied research, requirements generation, design, implementation, testing, integration, installation, and documentation.
• Stay current with state-of-the-art machine learning techniques and provide innovative ideas and approaches to solve challenging problems.