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"Research Assistant - Computational Pathology"

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Research Assistant - Computational Pathology

Research Assistant - Computational Pathology

Company:
Virginia Tech

Job Location:
Blacksburg, 24061

Category:
Laboratory and Research

Type:
Full-Time

Job Description

The Department of Biomedical Sciences and Pathobiology at the VA-MD College of Veterinary Medicine (Virginia Tech) is seeking a Research Assistant in Computational Pathology. This position involves developing and validating artificial intelligence-based image analysis pipelines for digital pathology applications.

The ideal candidate will be able to work independently on model development and validation while collaborating closely with pathologists to translate clinical questions into computational solutions.

The initial appointment is for two years, with potential extension based on performance and funding.

Responsibilities

  • Design and implement AI-driven image analysis pipelines for whole slide images (WSI)
  • Develop and validate deep learning models for tasks such as IHC quantification
  • Perform model validation against expert pathologist ground truth
  • Collaborate closely with pathologists and researchers to ensure biologically and diagnostically meaningful outputs

Required Qualifications

  • B.S. in computer science, data science, biomedical engineering, or a related field
  • Strong proficiency in Python and experience with deep learning frameworks (e.g., PyTorch or TensorFlow)
  • Demonstrated experience in image analysis and machine learning

Preferred Qualifications

  • Experience with whole slide imaging, digital pathology platforms, or histopathology-focused AI
  • Familiarity with CNN-based models, segmentation, or phenotyping tasks
  • M.S. or Ph.D. training (completed or in progress) in a relevant field
  • Experience working with microscopy or histopathology images and validating AI models

Pay Band
3; Salary

Overtime Status
Non-Exempt: Eligible for overtime

Appointment Type
Restricted

Salary Information
Commensurate with Experience

Hours per week
40, or as needed

Review Date
3/30/2026

Additional Information
The successful candidate will be required to have a criminal conviction check.

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