Staff Scientist – Quantitative MRI & Generative AI Cardiovascular Imaging

Position: Staff Scientist I – Quantitative MRI & Generative AI for Cardiovascular Imaging
** When you join the growing BILH team, you're not just taking a job, you’re making a difference in people’s lives.
** We are seeking a highly motivated Staff Scientist with expertise in artificial intelligence (AI), machine learning, and magnetic resonance imaging (MRI) to support and advance cutting-edge translational research in cardiovascular imaging. The successful candidate will play a central role in the research, development, and validation of AI-enabled methods, with a primary focus on quantitative imaging and diagnostic and prognostic applications.

Methodological efforts will leverage modern generative and vision-based models, such as generative adversarial networks (GANs), diffusion models, and transformer-based vision architectures, with an emphasis on robustness, reproducibility, and clinical relevance.

This position is well suited for a PhD-trained scientist who enjoys hands-on technical development, close collaboration with clinicians, engineers, and industry partners, and contributing to NIH-funded research programs. The role includes active collaborations with Siemens Healthineers and offers clear pathways toward clinical translation and real-world impact.

The successful candidate will have access to a well-established research infrastructure, including a state-of-the-art 3T Siemens MRI system for advanced cardiovascular imaging and a dedicated high-performance computing environment with NVIDIA H200 GPU clusters to support large-scale deep learning model development, training, and evaluation.

Applicants must hold a PhD in computer science, electrical engineering, or biomedical engineering and have a minimum of five years of research-based experience (including PhD thesis) in artificial intelligence, computer vision, or medical imaging in an academic or research environment.

Application Instructions:  In addition to a curriculum vitae (CV), applicants are required to upload one combined PDF file containing the following materials, organized in the order listed below:  
1. Cover letter describing research interests, relevant prior experience, career goals, and contact information for three references.  
2. Brief research statement outlining technical expertise, research contributions, and areas of interest related to AI and MRI.  3. Summary of relevant coursework (unofficial transcripts are encouraged).  4. Annotated summaries (approximately 4–6 sentences each) for the applicant’s most significant scholarly works. These summaries should describe the key findings, scientific impact, and the applicant’s specific role in each work. For middle-authorship contributions, applicants must clearly delineate their individual contributions.

All required application materials must be compiled into a single PDF file and uploaded at the time of application. Incomplete applications or applications that do not follow these submission instructions will not be considered.

Key Responsibilities:

AI & Imaging Research  
• Research and develop deep learning models for MRI reconstruction, segmentation, quantification, and image enhancement  
• Design, optimize, and evaluate AI pipelines to improve image acquisition efficiency, image quality, and robustness  
• Integrate AI methods with quantitative CMR imaging biomarkers, including myocardial blood flow, strain, and tissue characterization  
• Develop and apply methods for multi-modality data integration, combining imaging, physiologic signals (e.g., ECG), genetic, and clinical data for diagnostic and prognostic modeling  
• Perform rigorous model validation, including reproducibility testing, bias assessment, and external validation  
• Design, develop, and implement user-friendly software platforms for clinical deployment of AI-enabled imaging tools  Scientific Leadership  
• Serve as a technical lead on funded research projects (NIH R01s, industry collaborations)  
• Contribute to study design, statistical analysis plans, and imaging endpoints  
• Lead or co-author high-impact manuscripts, abstracts, and grant submissions  
• Mentor trainees (PhD students, postdocs, research staff) Data & Infrastructure  
• Build and maintain scalable AI/MRI pipelines (Python,…