Postdoctoral Associate

Job Description

Full-time (40 hours/week) Postdoctoral Associate in Computational Pathology at the Department of Biomedical Sciences and Pathobiology, Virginia-Maryland College of Veterinary Medicine (Virginia Tech). Focus on development and validation of AI-driven image analysis pipelines for digital pathology applications.

• Design and implement AI-driven image analysis pipelines for whole slide imaging (WSI), including convolutional neural networks (CNNs), visual transformers, and generative adversarial networks.
• Develop, optimize, and validate deep learning models for applications such as immunohistochemistry (IHC) quantification, segmentation, and phenotyping.
• Perform rigorous model validation against expert pathologist annotations and diagnostic ground truth.
• Collaborate closely with veterinary pathologists and interdisciplinary researchers to develop biologically and clinically meaningful computational tools.
• Assist in data management, model documentation, and preparation of manuscripts and presentations related to the research program.

• Ph.D. in computer science, data science, biomedical engineering, physics, or a closely related field. PhD must be awarded no more than four years prior to the effective date of appointment with a minimum of one year eligibility remaining.
• Strong programming proficiency in Python and experience with deep learning frameworks such as PyTorch or Tensor Flow.
• Demonstrated expertise in machine learning, deep learning, and image analysis.
• Ability to work independently while contributing effectively within a collaborative research environment.
• Ability to stand, stoop, bend, walk for a considerable amount of time.

• Experience with whole slide imaging, digital pathology platforms, or AI applications in histopathology.
• Familiarity with CNN-based architectures, segmentation approaches, phenotyping workflows, and/or visual transformers.
• Experience working with microscopy or histopathology datasets and validating AI models against expert annotations.
• Strong mathematical or computational modeling background.
• Evidence of peer-reviewed publications in relevant fields.

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

Virginia Tech does not discriminate against employees, students, or applicants on the basis of age, color, disability, sex (including pregnancy), gender, gender identity, gender expression, genetic information, ethnicity or national origin, political affiliation, race, religion, sexual orientation, or military status, or otherwise discriminate against employees or applicants who inquire about, discuss, or disclose their compensation or the compensation of other employees or applicants, or on any other basis protected by law.

If you are an individual with a disability and desire an accommodation, please contact Christina Pacholec at pacholec during regular business hours at least 10 business days prior to the event.