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Join our AI-focused internship to gain hands-on experience developing cutting-edge technology that detects manipulated images in academic publications and strengthens research integrity. This internship focuses on supporting the development of an AI-powered system designed to detect manipulated images and figures in academic publications and integrate it into editorial workflows. You will research and apply computer vision and image forensics techniques while assisting in building and evaluating machine learning and deep learning models to identify anomalies in scientific figures. The role offers hands-on experience collaborating with technical teams to manage datasets, improve model performance, and contribute to reliable image integrity detection solutions.
Job Responsibility:
Support the preparation of a proof-of-concept prototype capable of detecting image manipulations and its integration into the editorial workflows
Contribute to the development of an AI-driven system designed to detect various types of image and figure manipulations in academic publications
Conduct research and experimentation on computer vision and image forensics techniques, including duplication detection, splicing, retouching, and contrast or brightness alterations
Develop and evaluate machine learning and deep learning models (e.g., CNNs, autoencoders, transformers) for anomaly and similarity detection in scientific figures
Collect, preprocess and analyze image datasets extracted from academic manuscripts, ensuring data quality and representative coverage of manipulation types
Collaborate with data engineers and data scientists to design scalable training pipelines, manage large image datasets, and benchmark algorithmic performance
Explore and implement relevant open-source tools, datasets, and research methods in the field of digital image forensics
Document experimental results, model architectures, and findings, contributing to internal technical reports and presentations
Requirements:
Master’s degree in Data Science, Machine Learning, Artificial Intelligence, or a closely related field is required
a PhD in these areas is considered a strong advantage
Less than 2 years of professional or hands-on experience in Computer Vision, AI/Data Science, and Linux-based environments
Advanced proficiency in English, with strong written and verbal communication skills
Working knowledge of Microsoft O365 tools for documentation and collaboration
Basic proficiency in Python for building complex applications and developing machine learning models
Familiarity with technologies such as FastAPI, Celery, and Keycloak
Solid understanding of core Artificial Intelligence principles and methodologies
Hands-on exposure to deep learning frameworks such as PyTorch or TensorFlow for image analysis and model development
Experience using computer vision libraries including OpenCV, scikit-image, and Pillow for image preprocessing and feature extraction
Understanding of convolutional neural networks (CNNs) and modern vision architectures such as ResNet, Vision Transformers, and autoencoders
Foundational knowledge of image forensics and manipulation detection techniques, including error level analysis (ELA), copy-move detection, resampling analysis, and metadata inspection
Familiarity with image similarity and retrieval techniques such as feature embeddings and perceptual hashing
Basic exposure to containerization, DevOps, and MLOps tools including Docker, Kubernetes, Helm, Ansible, MLflow, and Kubeflow
Fundamental understanding of version control systems and CI/CD pipelines using Git
Strong problem-solving and analytical thinking skills
Excellent communication abilities with the capability to explain complex technical concepts to non-technical stakeholders
Ability to work effectively both independently and within a collaborative team environment
Comfortable operating in fast-paced, dynamic settings
Experience working within Scrum / Agile workflows, with a collaborative mindset and leadership potential
What we offer:
The opportunity to contribute to the academic/scientific community
Flexible working hours
Team bond strengthening through team-building events
Professional growth opportunities with our global training system
Working in a collaborative and socially responsible team
Company retreat facility
Full-coverage insurance for accidents/daily sickness
Prime location near Basel train station and city center
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