Postdoctoral Fellow in Machine Learning and Multimodal AI

We are looking for a strong, independent computational researcher who wants to develop original machine learning methods, shape their research direction, and collaborate closely with clinicians on meaningful healthcare problems.

Research opportunities

Our research integrates physiological signals, medical imaging, clinical text, and electronic health records, with applications in maternal and perioperative medicine. Potential directions include:

• Physiological time-series modeling: ECG, PPG, and hemodynamic waveforms, including temporal patterns and irregularly sampled clinical data.
• Computer vision and representation learning: Ultrasound and other medical imaging modalities.
• Multimodal learning: Integrating physiological signals, images, clinical text, and structured electronic health records.
• Robust and trustworthy ML: Model development, rigorous validation, generalizability, and translation to clinical prediction tasks.

Specific projects will be developed jointly around the fellow’s methodological strengths and research interests, aligned with the lab’s funded priorities.

What makes this opportunity distinctive?

Our lab combines close clinical collaboration, access to large-scale real-world clinical datasets, and established research infrastructure. We developed MERLIN, a scalable platform for clinical data processing and reproducible dataset generation, providing a foundation for research with complex, heterogeneous healthcare data.

The fellow will have opportunities to formulate original research questions, lead projects and publications, mentor junior researchers, and develop an independent research direction with clinical and computational mentorship.

• A PhD in computer science, engineering, statistics, applied mathematics, physics, or a related quantitative discipline, completed before the appointment begins.
• Strong Python programming skills and hands-on experience in machine learning or deep learning.
• Demonstrated ability to conduct original research, including rigorous experimental design, model evaluation, and scientific publication.
• Expertise in at least one relevant area, such as time-series modeling, computer vision, representation learning, NLP, or multimodal AI.

Prior clinical or healthcare experience is not required, and expertise across every modality is not expected. We particularly value scientific curiosity, creativity, and the ability to critically evaluate research findings.

The position is based in Boston, USA, with a hybrid working arrangement that includes on-site participation. International applicants are welcome., PhD or equivalent, PhD in computer science, engineering, statistics, applied mathematics, physics, or a related quantitative discipline, completed before the appointment begins.

Strong Python programming skills and hands-on experience developing and evaluating machine learning or deep learning models.

Research expertise in at least one relevant area, such as physiological time-series analysis, signal processing, computer vision, representation learning, natural language processing, or multimodal learning.

Evidence of original scientific contributions and the ability to lead a research project from question formulation through rigorous analysis and scientific communication.

Strong communication skills, a collaborative approach, and an interest in interdisciplinary research. Specific Requirements

Candidates should demonstrate thoughtful experimental design, rigorous model evaluation, and the ability to critically assess and verify their own code, analyses, and conclusions.

Experience with physiological waveforms, ultrasound, other medical imaging, or clinical datasets is welcome but not required. Prior clinical experience and expertise across all listed modalities are not expected.

Languages ENGLISH

The initial appointment is for one year, renewable annually subject to satisfactory performance and institutional requirements. The research program has five years of funding.

The advertised salary range is USD $73,544-$81,179 annually, depending on relevant experience and institutional policy.

The position offers clinical and computational mentorship, opportunities to lead publications and develop an independent research direction, and collaboration within an interdisciplinary research environment.

International applicants are welcome. J-1 visa sponsorship is available for eligible candidates, subject to institutional requirements.

This is a Boston-based hybrid position with on-site participation. Eligibility criteria

Applicants must complete their PhD before the appointment begins. Candidates from relevant quantitative disciplines are welcome, including those without previous healthcare research experience. Selection process