Postdoctoral Research Fellow in AIML for Multimodal Prognostication
Postdoctoral Research Fellow in AIML for Multimodal Prognostication
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Job Description
At Mass General Brigham we know it takes a surprising range of talented professionals to advance our missionfrom doctors nurses business people and tech experts to dedicated researchers and systems analysts. As a notforprofit organization Mass General Brigham is committed to supporting patient care research teaching and service to the community. We place great value on being a diverse equitable and inclusive organization as we aim to reflect the diversity of the patients we serve.
At Mass General Brigham we believe a diverse set of backgrounds and lived experiences makes us stronger by challenging our assumptions with new perspectives that can drive revolutionary discoveries in medical innovations in research and patient care. Therefore we invite and welcome applicants from traditionally underrepresented groups in healthcare people of color people with disabilities LGBTQ community and/or gender expansive first and secondgeneration immigrants veterans and people from different socioeconomic backgrounds to apply.
Job Summary
We at the Mass General Brigham NeuroAI Center are seeking a highly motivated Postdoctoral Research Fellow with expertise in machine learning (ML) and biomedical data analysis to contribute to cuttingedge research at the intersection of neuroscience critical care and computational modeling. This position will focus on developing advanced AI/ML models for prediction and outcome assessment in acute neurological conditions leveraging EEG EHR telemetry and neuroimaging data.Key Responsibilities:
Develop and validate multimodal AI/ML models integrating diverse clinical and physiological data.
Design and implement timeseries prediction frameworks utilizing transformerbased architectures ensemble learning and deep learning techniques.
Manage largescale electronic health record (EHR) EEG and telemetry datasets ensuring robust preprocessing feature extraction and handling of missing data.
Apply explainable AI (XAI) techniques such as SHAP and attention mechanisms to enhance model interpretability.
Implement validation strategies including nested crossvalidation conformal prediction for uncertainty quantification and adversarial training for model robustness.
Collaborate with a multidisciplinary team of clinicians data scientists and engineers to refine models for realworld deployment.
Contribute to manuscript preparation grant writing and dissemination of research findings at leading conferences and journals.
Qualifications
Qualifications:
Ph.D. in computer science biomedical engineering computational neuroscience applied mathematics or a related field.
Strong expertise in machine learning deep learning and statistical modeling with applications in biomedical data.
Experience with timeseries analysis transformers LSTMs and other temporal modeling techniques.
Proficiency in Python PyTorch and ML frameworks; experience with EHR data processing and feature engineering is a plus.
Familiarity with neurophysiological data (EEG telemetry) and neuroimaging analysis is highly desirable.
Strong publication record in AI/ML applications for healthcare or neuroscience.
Excellent problemsolving skills ability to work independently and strong collaborative mindset.
Excellent written and oral communication skills
Preferred Skills (Not Required but a Plus):
Proven ability to efficiently utilize cloud computing platforms (e.g. Azure AWS Google Cloud) and highperformance computing (HPC) clusters for scheduling assigning and managing computational research jobs.
Knowledge of selfsupervised learning and domain adaptation.
Familiarity with neurosciencerelated ML challenges such as predicting clinical deterioration or integrating multimodal physiological data.
What We Offer:
A dynamic interdisciplinary research environment at the forefront of AI in neuroscience and critical care.
Access to largescale clinical datasets and stateoftheart computational resources.
Opportunities to publish in toptier journals and present at leading conferences.
A collaborative and intellectually stimulating research team with strong clinical and computational expertise.
This is a fulltime and inperson position.
How to Apply:
Interested candidates should submit a single PDF file including:
Twopage CV detailing relevant experience and publications.
Onepage cover letter with exactly five bullet points each no more than two lines demonstrating your fit for this position.
Contact information for three references.
Applications will be reviewed on a rolling basis until the position is filled. For application submission and inquiries please contact:
When submitting your application please ensure the email subject line follows this format: Postdoc Application Your Full Name
Join us in advancing AIdriven precision medicine and neurological prognostication!
Additional Job Details (if applicable)
Remote Type
Work Location
EEO Statement:
Mass General Brigham Competency Framework
At Mass General Brigham our competency framework defines what effective leadership looks like by specifying which behaviors are most critical for successful performance at each job level. The framework is comprised of ten competencies (half PeopleFocused half PerformanceFocused) and are defined by observable and measurable skills and behaviors that contribute to workplace effectiveness and career success. These competencies are used to evaluate performance make hiring decisions identify development needs mobilize employees across our system and establish a strong talent pipeline.
Employment Type
Grant
