Intern

nference

Bengaluru, Karnataka, IndiaFresher1h agovia LinkedIn

This job at a glance

Who can apply
Freshers and up to 1 year · Bachelor's degree
Must know
Computer visionDeep learningPatient carePythonPyTorchTensorFlow
Nice to have
GitDockerAWSGCP
Work
On-site in Bengaluru · internship
Pay
Not stated by the employer.
Skill demand
Python14%of 22 similar fresher jobs posted in India this week
Listed
28 Oct 2026 · still open

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About the Role

  • Intern - Data Scientist (Medical Imaging and Computer Vision) role at nference.
  • Opportunity to gain hands-on experience developing AI models for healthcare challenges.

Key Responsibilities

  • Assist in developing and evaluating deep learning models for medical imaging (e.g., classification, segmentation, object detection).
  • Support image preprocessing, annotation, and data handling workflows involving DICOM and clinical image formats.
  • Help design and test pipelines for tasks like OCR, entity detection, and de-identification of sensitive medical data.
  • Collaborate with data scientists and medical experts to understand clinical requirements.
  • Participate in model validation, error analysis, and performance tuning.
  • Contribute to internal documentation, code organization, and reproducibility using tools like Git and Docker.

Requirements & Tech Stack

  • Python
  • At least one deep learning library (e.g., PyTorch, TensorFlow)
  • Basic knowledge of OpenCV, image processing, or model training workflows.
  • Git
  • Docker

Qualifications

  • Recent Bachelor’s or Master’s graduate in Computer Science, Biomedical Engineering, Electrical Engineering, or a related field.
  • Strong interest in computer vision and medical imaging.
  • Good problem-solving skills and willingness to learn.
  • Strong communication and team collaboration abilities.

Preferred Skills (Good To Have)

  • Academic or project exposure to medical imaging or OCR systems.
  • Basic understanding of Docker, Git, or cloud services (AWS/GCP).
  • Awareness of HIPAA, data privacy, or ethical AI practices.

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