Research internship

Harvard Medical School and Massachusetts General Hospital (MGH)

About the Role

Seeking highly motivated undergraduate/graduate students for a temporary research internship focused on advancing computational methods for medical imaging and exploring hybrid quantum-classical computing approaches for healthcare applications. The role is at the intersection of quantum computing, computational imaging, medical physics, artificial intelligence, and biomedical data science, contributing to research for PET/CT imaging and related technologies.

Key Responsibilities

• Assist in the development and evaluation of computational algorithms for large-scale medical imaging applications.
• Contribute to research involving hybrid quantum-classical computing frameworks.
• Implement, optimize, and benchmark algorithms using modern scientific computing tools.
• Support simulation studies, image analysis, and quantitative performance evaluation.
• Work with high-performance computing resources, GPU-accelerated computing environments, and emerging quantum computing platforms.
• Participate in research discussions, software development, manuscript preparation, and presentation of scientific results.

Requirements & Tech Stack

• Proficiency in Python and MATLAB programming.
• Familiarity with scientific computing, numerical methods, and data analysis.
• Strong analytical, mathematical, and problem-solving skills.
• Ability to work independently and collaboratively within an interdisciplinary research team.
• Strong written and verbal communication skills.

Qualifications

• Current undergraduate or graduate student in Computer Science, Physics, Electrical Engineering, Biomedical Engineering, Applied Mathematics, Data Science, Medical Physics, or a related field.
• Experience with medical imaging, image processing, signal processing, computational physics, or scientific computing is preferred.
• Experience with machine learning, optimization algorithms, or scientific software development is preferred.
• Familiarity with GPU computing, CUDA, parallel computing, or high-performance computing environments is preferred.
• Exposure to quantum computing concepts and/or frameworks such as Qiskit, CUDA-Q, PennyLane, Cirq, or related platforms is preferred.
• Previous research experience is preferred and encouraged.
• Interest in contributing to scientific publications and conference presentations is preferred.
• Interest in translational healthcare technologies and next-generation medical imaging systems is preferred.