Machine Learning Research Associate - MRI

Beth Israel Lahey Health•Boston, MA

10d•$27 - $38

About The Position

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 early-career technical research associate with strong interests in artificial intelligence (AI), machine learning, and magnetic resonance imaging (MRI) to join an interdisciplinary cardiovascular imaging research program. This position focuses on the development, implementation, and rigorous evaluation of machine learning and deep learning methods for advanced analysis of MRI data, with particular emphasis on cardiovascular imaging applications. The work will focus on the development of machine learning methods to improve quantitative imaging, including myocardial blood flow, quantitative biomarker estimation, and integration of imaging-derived metrics with physiologic and clinical data, leveraging modern generative and vision-based models such as generative adversarial networks, diffusion models, and transformer-based vision architectures. The research associate will participate in the design and maintenance of reproducible AI pipelines and research software, working with large-scale imaging, physiologic (e.g., ECG), and clinical datasets. Responsibilities include data curation and preprocessing, model training and validation, sensitivity analyses, performance benchmarking, and reproducibility assessment across datasets and experimental conditions. The role provides structured training in end-to-end AI research, spanning data management, model architecture design, experimental evaluation, and documentation, within the context of NIH-funded translational MRI studies. The research associate will work closely with faculty investigators, imaging scientists, and clinical collaborators and will contribute to peer-reviewed manuscripts, conference abstracts, and scientific presentations. 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 master’s degree in computer science, biomedical engineering or electrical engineering from a leading U.S. engineering or computer science institution and have a minimum of two years of research-based experience in machine learning in an academic or research environment. Applicants must be U.S. citizens or permanent residents, as required by the funding source. Application Instructions: In addition to a curriculum vitae (CV), applicants are required to submit a cover letter describing their prior experience in AI and machine learning research and career goals. Please include a summary of relevant coursework (e.g., deep learning, machine learning, computer vision, medical imaging, signal processing), as well as any prior research experience, including publications, preprints, software projects, or GitHub repositories, if available. Applicants are encouraged to upload relevant coursework and academic performance in related subjects. Applications submitted without a cover letter and relevant coursework will not be considered.

Requirements

Bachelor's degree in Life Sciences or related field required. Master's degree preferred.
3-5 years related work experience required.
Bachelor's degree and four years experience. Or, a Master's degree and two years experience.
Advanced skills with Microsoft applications which may include Outlook, Word, Excel, PowerPoint or Access and other web-based applications.
May produce complex documents, perform analysis and maintain databases.
Applicants must hold a master’s degree in computer science, biomedical engineering or electrical engineering from a leading U.S. engineering or computer science institution and have a minimum of two years of research-based experience in machine learning in an academic or research environment.
Applicants must be U.S. citizens or permanent residents, as required by the funding source.

Responsibilities

Functions as a principal technical specialist for a research laboratory or for a specific research project.
Functions as an internal consultant and as a resource to other labs both internally and externally.
Performs and devises specialized tests and research procedures, troubleshooting problems of own and other researchers' results.
Conducts broad range of experiments involving advanced technology.
Participates in the design of experimental protocols to achieve the objective of the research project.
May prioritize work and assign work to lower-level technical personnel.
May instruct laboratory techniques and methodology to students and other research personnel.
May be involved in complex data analysis and interpretation of results.
Collaborates with supervisor in writing and editing materials for publication.
May assist in preparing manuscripts and writing abstracts.
May write portion(s) of grant application, e.g.: Materials and Methods, or Experimental Design.
May present papers at society meetings.
Attends conferences and courses, consults with other researchers and participates in professional activities to keep abreast of the latest technological developments as they relate to the research.
Evaluates the applicability of these new developments and implements their use in collaboration with the principal collaborator.