nFerence is hiring for an fresher entry level Data Scientist INTERN role in India

Position:

Intern – Data Scientist (Medical Imaging and Computer Vision)

Company:

nFerence

Location:

Bengaluru, India

Job type:

Full-Time

Job mode:

On-site

Job requisition id:

Not disclosed

Years of experience:

0–1 years

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Company Description:

• nFerence is a cutting-edge AI company focused on biomedicine, known informally as the "Google of Biomedicine".

• The company is creating a scalable computing platform that integrates clinical texts, biomedical signals, and medical imaging for real-world applications.

• Collaborates with prominent medical institutions like Mayo Clinic to derive insights from medical datasets including radiology images and electronic health records.

• The team includes world-class professionals and researchers from institutions such as MIT, Harvard, IITs, and IISc.

• The company’s mission is to accelerate pharmaceutical innovation and improve early disease detection using AI and deep learning.

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Profile Overview:

• The role is designed for highly motivated individuals eager to work at the intersection of healthcare and artificial intelligence.

• Interns will contribute directly to the development of AI models focused on medical imaging and computer vision.

• The opportunity allows hands-on involvement in projects related to disease classification, image segmentation, and object detection in clinical data.

• Candidates will join a multidisciplinary team consisting of data scientists, engineers, and medical professionals.

• The experience includes working on real healthcare challenges and contributing to solutions that impact patient outcomes.

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Qualifications:

• Candidates should be recent graduates (Bachelor’s or Master’s) in fields like Computer Science, Biomedical Engineering, or related disciplines.

• A strong interest in AI, computer vision, and medical imaging is essential.

• Working knowledge of Python is expected, along with familiarity with deep learning frameworks like PyTorch or TensorFlow.

• Experience with image processing tools or libraries such as OpenCV is desirable.

• Candidates must demonstrate effective problem-solving skills and the ability to work well in team environments.

• Good communication and a willingness to engage in collaborative learning are important attributes.

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Additional Info:

• Interns will be involved in AI model training and validation pipelines used in medical imaging applications.

• Work includes tasks such as OCR pipeline design, entity recognition, and data anonymization.

• Training will include tools like Git and Docker to ensure reproducibility and code management.

• Candidates may gain experience with handling clinical image formats such as DICOM.

• The role is a unique opportunity to gain exposure to advanced AI applications in real-world healthcare settings.

• Exceptional interns may be offered a transition to full-time roles based on performance and organizational needs.

• The internship offers mentorship from seasoned experts and access to industry-grade datasets and computing resources.

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Roles and Responsibilities 

Involvement in AI and Deep Learning Model Development

• Support the creation and refinement of machine learning models focused on analyzing medical images.

• Contribute to tasks such as disease detection, object localization, and segmenting regions of interest in scans.

• Explore AI techniques applicable to clinical data and participate in their real-time deployment.

Preprocessing and Annotation of Medical Images

• Assist in the end-to-end pipeline of handling clinical images, including formatting, cleaning, labeling, and storage.

• Work with formats like DICOM and understand workflows for managing clinical imaging datasets.

• Engage in annotation tasks that require medical knowledge and apply technical strategies to optimize these workflows.

Design of OCR and Data De-identification Systems

• Contribute to the development of optical character recognition modules.

• Support entity recognition systems that extract useful clinical terms or identifiers from scans or documents.

• Ensure sensitive health information is properly anonymized before usage or model training.

Cross-functional Team Collaboration

• Engage with a team of data scientists, software engineers, and clinical practitioners.

• Understand clinical priorities and tailor model objectives to solve specific healthcare problems.

• Participate in brainstorming sessions and contribute ideas to ongoing research and model development.

Model Evaluation and Iterative Improvements

• Assist in measuring model performance using metrics such as accuracy, recall, and precision.

• Perform error analysis to identify underperforming cases and suggest improvements.

• Use performance insights to optimize training strategies or data pipelines.

Documentation and Tooling

• Follow best practices in organizing research code and results.

• Use version control systems like Git for code tracking and collaboration.

• Employ Docker for creating containerized environments that ensure consistent experiment results across systems.

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Skills Required

Must-Have Skills:

• Proficiency in Python

• Familiarity with deep learning libraries like PyTorch or TensorFlow

• Understanding of image processing workflows

• Basic experience with OpenCV

• Ability to work independently and in collaborative team settings

Good to Have:

• Exposure to medical imaging or OCR systems during academic or project work

• Hands-on experience with Git, Docker, or cloud platforms like AWS/GCP

• Awareness of healthcare compliance and privacy standards such as HIPAA

• Interest in ethical AI development and real-world impact of model outputs

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Learning and Growth Opportunities

• Get mentorship from globally recognized professionals in medical AI.

• Direct involvement in projects with tangible health outcomes.

• Work in a dynamic and learning-intensive atmosphere with access to high-quality infrastructure.

• Chance to explore cutting-edge developments in medical image analysis and AI.

• Build a career foundation with the possibility of being absorbed into full-time roles.

Please click here to apply.