Research Assistant

Research Assistant

Apply now Job no: 502566
Work type: Full-Time
Location: University City - Philadelphia, PA
Categories: Drexel University, College of Engineering

Job Summary

Integrate optically simulated images and generative models to augment image datasets of small objects for enhanced detection performance of computer vision algorithms. Document the findings and publish the results in journals and conferences.

Essential Functions

• Conduct research to design machine learning algorithms for detection of small objects.
• Explore innovative approaches by incorporating simulated images generated through graphics rendering engines like Unreal Engine to augment the training data for detection algorithms.
• Additionally, conduct in-depth research to leverage advanced techniques, such as Generative Adversarial Networks (GANs) or other generative algorithms, to convert simulated images into highly realistic images for algorithm training.
• The end goal is to integrate optically simulated images and generative models to augment image datasets of small objects for enhanced detection performance of computer vision algorithms. Document the findings and publish the results in journals and conferences.

Required Qualifications

• A master's degree in electrical and computer engineering/or Comparable are of focus is required.
• 0-1 years of relevant experience is required.
• Machine learning based computer vision. is required.

Physical Requirements

• Typically sitting at a desk/table
• Typically standing, walking

Location

• University City – Philadelphia, PA

Additional Information

This is a full-time, temporary position classified as Non-Exempt.  The offered pay is based on the successful candidate’s qualifications and experience, department budget, and an internal equity review. 

For information about benefits, please review Drexel’s Per Diem/Casual/Temporary Benefit Fact Sheet .

Special Instructions to the Applicant

Please make sure you upload your CV/resume and cover letter when submitting your application.

Review of applicants will begin once a suitable candidate pool is identified.

Advertised: Jan 31 2024 Eastern Standard Time
Applications close: Feb 26 2024 Eastern Standard Time

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