Postdoctoral AI/ML Researcher—Medical Image Analytics

University-of-North-Carolina-At-Chapel-Hil

Chapel Hill (NC)

Vor Ort

USD 70.000 - 95.000

Vollzeit

Vor 3 Tagen
Sei unter den ersten Bewerbenden

Eine vollständige Bewerbung in einer Minute

Maßgeschneiderter Lebenslauf und Anschreiben – versandbereit.

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Zusammenfassung

University of North Carolina at Chapel Hill seeks a Postdoctoral Research Associate to conduct advanced research in AI, machine learning, computer vision, and medical image analysis. You will design and evaluate algorithms, curate large clinical datasets, and develop reproducible pipelines for validation.

The position emphasizes leadership in research activities, publication, and grant support, with opportunities to mentor students and collaborate with radiology, cardiology, and population

Qualifikationen

  • PhD in Computer Science, Biomedical Engineering, Electrical or Computer Engineering, Data Science, Applied Mathematics, or related field.
  • Doctoral degree must be completed before the proposed start date.
  • Strong programming in Python and experience with PyTorch or TensorFlow.

Aufgaben

  • Conduct advanced research in AI, ML, computer vision, and medical image analysis.
  • Develop reproducible computational pipelines; processing and curating large datasets.
  • Lead or contribute to peer-reviewed publications, conference presentations, and reports.
  • Mentor graduate and undergraduate researchers; collaborate across disciplines.

Kenntnisse

Machine learning
Deep learning
Medical image analysis
Computer vision
Biomedical data science
Python
Communication

Ausbildung

PhD or equivalent doctoral degree

Tools

PyTorch
TensorFlow

Jobbeschreibung

University of North Carolina at Chapel Hill seeks a Postdoctoral Research Associate to conduct advanced research in AI, machine learning, computer vision, and medical image analysis. You will design and evaluate algorithms, curate large clinical datasets, and develop reproducible pipelines for validation.

The position emphasizes leadership in research activities, publication, and grant support, with opportunities to mentor students and collaborate with radiology, cardiology, and population

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