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Rachel Buckley

4 months ago

Postdoctoral Opportunity in Machine Learning, Deep Learning, and Multimodal Prediction for Alzheimer’s Disease Risk Mass General Brigham in United States

Degree Level

Postdoc

Field of study

Computer Science

Funding

Postdoctoral opportunity within the Buckley Lab and the Harvard Aging Brain Study Data & Informatics Team at Mass General Brigham. The post is described as a postdoctoral fellowship/opportunity; no stipend, salary, tuition, or other funding amount is specified in the post.

Deadline

Expired

Country flag

Country

United States

University

Massachusetts General Hospital

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Keywords

Computer Science
Machine Learning
Biomedical Engineering
Information Technology
Biostatistics
Deep Learning
Biology
Mathematics
Cognitive Neuroscience
Alzheimer's Disease
Neuropsychology
Medical Science
Statistics
Bioinformatic
Applied Mathematic

About this position

Postdoctoral opportunity in machine learning, deep learning, and multimodal prediction for Alzheimer’s disease risk at Mass General Brigham, within the Buckley Lab and the Harvard Aging Brain Study Data & Informatics Team.

This role is designed for a highly quantitative researcher who wants to apply advanced computational methods to rich longitudinal biomedical data. The project focuses on large-scale data science and clinically translational research in Alzheimer’s disease, including deep phenotyping, cross-cohort data integration, disease heterogeneity, and modeling of expected vs. observed disease trajectories.

Research topics mentioned include multimodal prediction models, artificial neural networks, survival/time-to-event modeling, clustering, latent subgroup discovery, interpretable machine learning, model validation, generalizability, domain adaptation, uncertainty quantification, and handling missingness and cohort heterogeneity. The work uses harmonized multi-cohort data from more than 10 international aging and AD cohorts, including clinical, cognitive, neuroimaging, blood biomarker, vascular, and demographic data.

Ideal applicants have a PhD in computer science, bioinformatics, applied mathematics, biostatistics, computational neuroscience, engineering, or a related quantitative field. Strong programming and scientific writing skills are expected. Experience with Alzheimer’s disease or neurology is helpful but not required.

The post emphasizes teamwork, curiosity, and strong technical expertise. The environment includes close collaboration with Dr. Timothy Hohman and Dr. Michael Donohue, plus interaction with the broader Mass General Brigham and Harvard communities and other international collaborators.

To apply, send a CV and a 1-page cover letter describing your technical skills, career goals, and fit with the position. No deadline or funding amount is specified in the post.

Funding details

Postdoctoral opportunity within the Buckley Lab and the Harvard Aging Brain Study Data & Informatics Team at Mass General Brigham. The post is described as a postdoctoral fellowship/opportunity; no stipend, salary, tuition, or other funding amount is specified in the post.

What's required

Applicants should have a PhD in computer science, bioinformatics, applied mathematics, biostatistics, computational neuroscience, engineering, or a related quantitative discipline. Strong candidates should understand how to translate scientific questions into regression, classification, survival/time-to-event, clustering, and other prediction tasks, and be familiar with model regularization, hyperparameter optimization, cross-validation, model selection, and evaluation. Strong programming, data science, scientific writing, and organizational skills are essential. A background in Alzheimer’s disease or neurology is beneficial but not necessary.

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Professors

Associate Professor of Neurology

University Name
Country flag

United States

Research Interests

Neuropsychology

Neurology

Alzheimer's Disease

Neurodegenerative Disease

Cognitive Aging