Anatomy / Medicine / Physiotherapy Student

Requirements

• Anatomy/Medicine/Physiotherapy student or practitionerMust
• Knowledge of hand anatomy and joint nomenclature (wrist, MCP, PIP, DIP, CMC, IP)Must
• Attention to detail and precision in anatomical landmark placementMust
• Ability to follow strict annotation guidelines and protocolsMust
• Ability to work remotely and independentlyMust
• Domain expertise in human anatomyMust
• Experience or comfort with digital annotation tools

What you'll do

• Annotate hand and finger landmarks using MediaPipe-style hand topology
• Identify and mark anatomical joints with precision and accuracy
• Place landmarks following defined annotation protocols and tolerance thresholds
• Infer and annotate partially occluded or visually challenging joints
• Interpret hand poses, orientations, and perspectives across varied data
• Review visual feedback and identify deviations from requirements
• Make targeted corrections to maintain annotation quality at scale
• Reason through complex hand positions and object interactions

Keywords

About the role

Role Title: Anatomy / Medicine / Physiotherapy Student Role Type: Contractor Location: Remote micro1 is engaging Anatomy / Medicine / Physiotherapy Students to contribute specialized knowledge on a customer’s advanced annotation project. In this role, you'll apply your expertise to help train next-generation AI systems. Your work will shape how models learn, reason, and perform through high-quality, real-world input. No prior experience in AI is required — your domain knowledge is what matters. Scope of Work • Annotate hand and finger landmarks/keypoints using MediaPipe-style hand topology, ensuring accuracy and adherence to strict guidelines. • Identify and mark anatomical joints, including the wrist, MCP (Metacarpophalangeal), PIP (Proximal Interphalangeal), DIP (Distal Interphalangeal), fingertips, and thumb-specific joints (CMC, MCP, IP, thumb tip). • Precisely place landmarks following defined annotation protocols and specified tolerance thresholds. • Infer and accurately annotate partially occluded or visually challenging joints and landmarks, reasoning through complex hand positions and object interactions. • Interpret a wide range of hand poses, orientations, and perspectives to ensure consistent and high-quality annotations across varied image and video data. • Review visual feedback, identify deviations from requirements, and make targeted corrections to maintain annotation quality at scale. Originally posted on Himalayas