Harvard Medical School Post Doctoral Fellow in AI/Deep Learning for Biology

[Georg Gerber]

The Gerber Lab (http://gerber.bwh.harvard.edu) at Brigham and Women’s Hospital/Harvard Medical School develops novel computational methods and high-throughput experimental systems to understand complex biological systems. In particular, we study the microbiome and its role in human disease. The microbiome, or trillions of micro-organisms living on and within us, is critical for human health and when disrupted, can contribute to a variety of disorders including neurological, gastrointestinal, and metabolic diseases, infections, autoimmunity, and cancer. A long-standing and continuing focus of the lab is on incorporating principled probabilistic models into machine learning methods and co-designing biological experiments to provide maximally informative data to models. The director of the lab, Dr. Georg Gerber, MD, PhD, MPH, uses his unique expertise, combining deep learning method development, medical microbiology, and human pathology, to leverage cutting-edge technologies to tackle scientifically and clinically important problems.

We are looking for an exceptional researcher who will play a major role in initiatives in the lab to develop novel artificial intelligence (AI)/deep learning (DL) approaches to further understanding of the microbiome. Areas of interest include developing new probabilistic AI/DL approaches to analyze multi-modal (e.g., sequencing, metabolomics, spatial-omics) time-series data while incorporating prior biological knowledge, and leveraging AI/DL techniques such as LLMs to facilitate interpretation and application of results.

The successful candidate will be highly motivated and creative, taking a lead role in developing new AI/DL-based methods, analyzing data, and interpreting results. Although experience analyzing data from biological systems is required, microbiome specific knowledge is not. This position is a great opportunity for an individual with EITHER a strong machine learning background who wants to get domain-specific research experience, OR someone with a strong mathematical background (e.g., Applied Math, Statistics or Physics PhD) who wants to get more machine learning experience.

Qualifications:
• PhD in Computer Science, Computational Biology, Mathematics, Physics, Statistics, or other highly quantitative discipline.
• Outstanding publication track record.
• Strong mathematical background and skills.
• Experience developing DL methods.
• Experience analyzing data from biological systems.
• Solid programming skills in Python, including PyTorch.
• Superior verbal and written communication skills, and ability to work on multidisciplinary teams.

Environment:  the Gerber Lab is located in the Brigham and Women’s Hospital Division of Computational Pathology (http://comp-path.bwh.harvard.edu) at Harvard Medical School (HMS). With a recent grant from the Massachusetts Life Science center, the Division has built the Lab for AI/Deep Learning for the Microbiome, which has a state-of-the-art GPU cluster for model development, training and deployment. BWH is part of the greater Longwood Medical Area in Boston, a rich, stimulating environment conducive to intellectual development and research collaborations, which includes HMS, Harvard School of Public Health and Boston Children’s Hospital.

To apply: email a single PDF including cover letter, CV, brief research statement and a list of at least three references to Dr. Georg Gerber (gge...@bwh.harvard.edu).

We are an equal opportunity employer and all qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, disability status, protected veteran status, gender identity, sexual orientation, pregnancy and pregnancy-related conditions or any other characteristic protected by law.