Research Scientist Intern – Human-Centric Generative AI

This position requires highly-motivated individuals who want to join us in the fast-moving field of large-scale models for human-centric 3D representations. You will be responsible for developing implementing evaluating and improving computer vision and GenAI algorithms that model photorealistic humans in complex and diverse internship areas : Human-centric video diffusion models3D reconstruction of humansHuman-centric generative modelsFace and body trackingHuman-object InteractionAdvanced neural rendering techniquesNeural simulation techniquesPower-efficient deep learning

• Strong understanding of modern machine learning techniques (e.g. generative multi-modal and foundational models video understanding and self-supervised learning).
• Strong understanding of modern approaches for 3D reconstruction and rendering (e.g. MVS NeRF Gaussian Splatting).
• Fluency in Python and Machine Learning frameworks (e.g. PyTorch) is required.
• Excellent communication and collaboration skills.
• Good problem solving and analytical thinking abilities.
• Working towards a MSc or PhD degree in Computer Science or a related field. PhD students are preferred for research-focused internships.
• At the end of the internship you must return to university to continue your education or the internship must be the last requirement for you to graduate.
• Hands-on experience with image or video diffusion models 3D generative models Gaussian splatting or vision foundation models.
• Hands-on experience with human modeling algorithms (e.g. skeletal tracking body shape and pose models hair and garment modeling).
• Publication record at top conferences such as CVPR ECCV ICCV NeurIPS or SIGGRAPH is a plus.
• Availability for 6 months minimum is preferred.
• Industry experience is a plus.

Required Experience :

Intern

Key Skills

Robotics,Machine Learning,Python,AI,C / C++,Data Collection,Research Experience,Signal Processing,Natural Language Processing,Computer Vision,Deep Learning,Tensorflow

Employment Type : Intern

Experience : years

Vacancy : 1