About the Role
Train artificial intelligence models to interpret and generate graphical abstracts in the field of physics by providing accurate annotations, feedback, and structured data inputs.
Responsibilities
- Annotate physics-related graphical abstracts with precise scientific labels
- Evaluate AI-generated visual summaries for technical accuracy
- Provide feedback to improve model performance on physics concepts
- Follow detailed guidelines for data consistency and quality
- Identify and flag inaccuracies in diagrams and visual representations
- Collaborate with project leads to refine training protocols
- Maintain high standards of data integrity across assigned tasks
- Review schematic representations of physical phenomena
- Assist in developing training benchmarks for visual understanding
- Ensure alignment between textual and graphical scientific content
- Classify visual elements according to physics domains
- Support iterative improvements to AI interpretation of figures
- Adhere to project timelines and quality benchmarks
- Participate in calibration exercises with other annotators
- Document edge cases in graphical representation
- Contribute to the refinement of annotation taxonomies
- Verify units, scales, and physical relationships in diagrams
- Assess clarity and scientific validity of visual abstractions
- Work with multimodal datasets combining text and images
- Report technical issues in the training interface
Compensation
Competitive hourly rate
Work Arrangement
Remote
Team
Collaborative, interdisciplinary team focused on AI model development
Project Focus
- Specialized training on graphical abstracts from physics literature
- Focus on improving AI comprehension of visual scientific data
Work Schedule
- Flexible hours with expectation of regular weekly availability
- Tasks distributed in batches with defined deadlines
Not available