Overview

The Fellow will work in a multi-disciplinary team of machine learning scientists, informaticians, biostatisticians and clinicians led by Dr. Marinka Zitnik and Dr. Alexander Turchin on projects involving development of predictive models in medicine leveraging temporal and longitudinal data. Explainable AI models will be based on data from a large integrated healthcare system and will utilize a combination of artificial intelligence and natural language processing of multiple narrative document streams.

Location

Brigham and Women’s Hospital and Harvard Medical School

Qualifications

We seek a highly motivated individual with background in deep learning and / or large-scale knowledge graphs and / or large language models; experience working with large datasets, ability to design and conduct effective research studies; strong analytical, scientific writing, presentation and communication skills; strong programming and system development skills; working knowledge of deep learning frameworks, such as PyTorch; and working knowledge of SQL.

Experience with predictive modeling, natural language processing, medical terminologies and ontologies is a strong plus. Successful applicants will be strong technically as well as have an inclination towards real-world problems.

Candidates must have a Ph.D. or equivalent degree in computer science, statistics, biomedical informatics, computational biology or a closely related field.

Application process

The position is available immediately and can be renewed annually. Interested applicants should submit the following documents via email to Dr. Alexander Turchin and Prof. Zitnik and use the subject line “Postdoctoral Fellowship in Machine Learning / Predictive Modeling”:

• Curriculum Vitae (please include links to your academic webpage and any software you developed, e.g., GitHub repositories)
• Two representative publications (preprints are acceptable)
• Statement of Research (2 pages) describing prior research experience and future research plans

Letters of recommendation will be solicited after the initial review. We are currently reviewing applications for this position. Interested candidates are encouraged to submit their applications as soon as possible.

Harvard is an Equal Opportunity Employer.