About the Role
Job Summary:
We are looking for an MRI Engineer to support the development, integration, and maintenance of advanced MRI technologies. The ideal candidate will focus on optimizing MRI pulse sequences, troubleshooting MRI system performance, and ensuring the seamless implementation of new diagnostic tools like the MRH (Magnetic Resonance Histopathology). You will collaborate with software developers, clinicians, and R&D teams to ensure high-quality imaging and data acquisition in both clinical and research settings.
Key Responsibilities:
Develop and optimize MRI pulse sequences for enhanced diagnostic capabilities.
Ensure MRI system calibration, maintenance, and troubleshooting.
Collaborate on integrating new MRI technologies with software and hardware platforms.
Conduct system performance tests and quality assurance on MRI protocols.
Provide technical support for MRI installations and upgrades.
Ensure regulatory compliance and safety standards in MRI operations.
Requirements
Qualifications:
Bachelor's or Master's degree in Biomedical Engineering, Electrical Engineering, or related field.
Experience with MRI systems, pulse sequence development, and medical imaging protocols.
Strong knowledge of MRI physics, imaging techniques, and data processing.
Experience with DICOM protocols and PACS systems is a plus.
Excellent problem-solving and communication skills.
Preferred Qualifications:
Experience in medical imaging, clinical trials, or healthcare environments.
Familiarity with MRI safety protocols and regulatory requirements.
Proficiency in MRI software and image processing algorithms.
About the Company
BioProtonics is a pioneering company focused on advancing diagnostic imaging through its Magnetic Resonance Histopathology (MRH) technology. MRH offers a non-invasive, high-resolution method for analyzing tissue microarchitecture during routine MRI scans. By capturing detailed spectral data across various wavelengths, MRH provides valuable insights into tissue health, helping differentiate between normal and potentially diseased or cancerous tissues. This innovative approach aims to enhance early disease detection, reduce the need for invasive biopsies, and improve patient care through more precise diagnostic capabilities.