Intern - Data Scientist (Medical Imaging and Computer Vision)
nference · Bengaluru · onsite · Posted 1d ago
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About this role
Job Title
Intern - Data Scientist (Medical Imaging and Computer Vision)
Location:
On-site Bengaluru
About Us
At nFerence Labs, often referred to as the Google of Biomedicine (see nference.ai/news for our latest research), we are building a large-scale pharmaco-biomedical computing platform. Using cutting-edge AI and Deep Learning on clinical text, medical images, and other biomedical signals, we aim to accelerate drug discovery and enhance early disease detection.
We work closely with leading medical institutions like the Mayo Clinic to extract insights from medical data—such as radiology images, patient notes, and lab results. Our team consists of top-tier talent from institutions like MIT, Harvard, IITs, IISc, and more, combining expertise in computer science, biomedical research, and clinical medicine.
About The Role
We are looking for a motivated Data Science Intern to join our Medical Imaging and Computer Vision team. This internship offers a unique opportunity to gain hands-on experience developing AI models that solve real-world 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.
Required Skills And 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.
Familiarity with Python and at least one deep learning library (e.g., PyTorch, TensorFlow).
Basic knowledge of OpenCV, image processing, or model training workflows.
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.
What We Offer
Work on impactful healthcare AI projects.
Mentorship from experienced professionals in AI, clinical research, and medical imaging.
A collaborative and fast-paced learning environment.
Access to world-class datasets and compute infrastructure.
Possibility of full-time conversion based on performance and project needs.
Intern - Data Scientist (Medical Imaging and Computer Vision)
Location:
On-site Bengaluru
About Us
At nFerence Labs, often referred to as the Google of Biomedicine (see nference.ai/news for our latest research), we are building a large-scale pharmaco-biomedical computing platform. Using cutting-edge AI and Deep Learning on clinical text, medical images, and other biomedical signals, we aim to accelerate drug discovery and enhance early disease detection.
We work closely with leading medical institutions like the Mayo Clinic to extract insights from medical data—such as radiology images, patient notes, and lab results. Our team consists of top-tier talent from institutions like MIT, Harvard, IITs, IISc, and more, combining expertise in computer science, biomedical research, and clinical medicine.
About The Role
We are looking for a motivated Data Science Intern to join our Medical Imaging and Computer Vision team. This internship offers a unique opportunity to gain hands-on experience developing AI models that solve real-world 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.
Required Skills And 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.
Familiarity with Python and at least one deep learning library (e.g., PyTorch, TensorFlow).
Basic knowledge of OpenCV, image processing, or model training workflows.
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.
What We Offer
Work on impactful healthcare AI projects.
Mentorship from experienced professionals in AI, clinical research, and medical imaging.
A collaborative and fast-paced learning environment.
Access to world-class datasets and compute infrastructure.
Possibility of full-time conversion based on performance and project needs.
Sourced from foundit
Skills
DockerDICOMOpencvPytorchTensorflowPythonOCRDeep LearningGIT
About nference
nference
Software Product
216
employees
2013
13 years old
Cambridge, Massachusetts
United States of America
₹23.3L PA avg
Avg at nference
About
Develops computational platforms to interpret biomedical knowledge, enhancing drug discovery and disease diagnosis through data analytics.
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Software Product
Employee ratings
10 reviews
3.3/ 5
Culture
3.4
Career growth
2.4
Work-life
3.1
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