Research Data Analyst, Heart Vascular Institute

We are seeking a research assistant to develop and deploy advanced deep learning and computer vision systems for multimodal surgical data analysis and augmented reality (AR) applications. This position involves building end-to-end AI pipelines that integrate video, imaging, and textual data for intraoperative guidance, surgical education, and clinical decision support. You will work with laparoscopic video, CT/MRI data, 3D models, and point clouds to develop automated tools for segmentation, registration, depth estimation, and 3D visualization. The role also includes building retrieval-augmented generation (RAG) systems around local large language models (LLMs) for secure processing of confidential clinical data.
You will collaborate closely with cardiac surgeons, postdoctoral researchers, and computational scientists to translate clinical ideas into working AI-driven systems, contributing directly to publications and translational research initiatives.

Required Qualifications

* Strong programming and software engineering skills, with expertise in Python and deep learning frameworks such as PyTorch and TensorFlow.

* Experience with computer vision and medical imaging libraries (OpenCV, scikit-image, 3D Slicer, ParaView).
* Familiarity with 3D modeling, registration, and mesh processing (.stl, .obj) and AR frameworks (Unity, Apple ARKit).
* Background in training, deploying, and benchmarking ML models for segmentation, phase recognition, or depth estimation.
* Proficiency in building RAG systems, vector databases, and local LLM deployments, ensuring data privacy and confidentiality.
* Experience with cloud and on-premise environments, including GPU clusters, Docker, Proxmox, and AWS.
* Bachelor's degree in Computer Science, Biomedical Engineering, or a related technical field with strong knowledge of machine learning and AI.

Knowledge, Skills and Abilities
- Understanding of human pathophysiology, hematologic function, pregnancy physiology and related fields of study.
- Understanding of mathematical modeling, including dynamical systems, statistical analysis, and computational methods.
- Ability to work collaboratively as part of a team and with supervision from team members.
- Ability to work productively with scientists and clinicians at all levels.
- Works in an organized manner with the ability to follow instructions, processes and timelines.
- Can identify roadblocks occurring within areas of responsibility and refer them to the appropriate party(s) for assistance.
- Strong computer skills, including accurate data entry.

What We Offer
* Hands-on experience at the intersection of AI, surgery, and biomedical imaging within a collaborative environment at Harvard Medical School.
* Mentorship from cardiac surgeons, postdoctoral researchers, and computational scientists on high-impact translational projects.
* Opportunities to lead and co-author publications, present at conferences, and develop tools used directly in clinical and research workflows.
* A dynamic, research-intensive yet startup-like environment that values innovation, independence, and cross-disciplinary collaboration.