"Research Assistant in AI-enabled Healthcare Applications"

Description

The Prof. Sunil Kumar’s Research Group in the Division of Engineering, New York University Abu Dhabi, seeks to recruit a research assistant to develop AI-enabled healthcare applications.

Key Responsibilities:

• Develop and fine-tune computer-vision models, instance segmentation, and retrieval-based estimation from images and text metadata.
• Build and evaluate monocular depth pipelines and implement multimodal retrieval with re-rankers for robust profile selection.
• Design and train advanced AI models for digital twin: 3D model learning, prediction models from imaging and molecular data, model-based simulation coupling, and uncertainty-aware outputs for lab/clinical validation.
• Work with 3D datasets, time-series sensors, and multi-omics or assay data to create predictive models and digital twin prototypes.
• Maintain reproducible code, experiments, and model/dataset versioning; develop deployment artifacts (Docker, CI/CD scripts) and support cloud/HPC model training.
• Plan, run and analyze pilot studies (SME pilots and lab validation); participate in data collection, annotation and lab assay coordination.
• Write up results and contribute to publications, technical reports and presentations for academic and non-academic stakeholders.

Minimum Qualifications:

• Bachelor’s or Master’s degree in computer science, electrical/computer engineering, applied mathematics, computational biology, bioengineering, or a closely related discipline.
• Solid experience training and evaluating AI models.
• Proficiency in Python and ML frameworks (PyTorch, TensorFlow).
• Experience with dataset curation, annotation workflows, FAISS/embedding retrieval, LLM-based parsing, RAG-style pipeline, and GPU/HPC training.
• Familiarity with 3D data processing or willingness to learn quickly.
• Publications, thesis work, or demonstrable projects in computer vision, multi-modal ML, digital twins or biomedical ML.
• Familiarity with uncertainty quantification and model explainability methods.
• Strong software engineering practices: Git, reproducible experiments, modular code, deploying models in cloud (AWS/GCP) and containerized services (Docker, Kubernetes).
• Good written and verbal communication skills and ability to work collaboratively across interdisciplinary teams.

For consideration, applicants need to submit a cover letter, curriculum vitae with full publication list statement of research interests, transcript and three letters of reference, all in PDF format. If you have any questions, please email Prof. Prabodh Panindre at prabodh@nyu.edu.

The terms of employment are very competitive and include housing and educational subsidies for children. Applications will be accepted immediately and candidates will be considered until the position is filled.