Job Description

The Team

CZI supports the science and technology that will make it possible to help scientists cure, prevent, or manage all diseases by the end of this century. While this may seem like an audacious goal, in the last 100 years, biomedical science has made tremendous strides in understanding biological systems, advancing human health, and treating disease.

Our vision is to build the future of science by advancing biomedical research and leveraging advances in AI. Over the next 10 years, we’re working to understand the mysteries of the cell, which we believe will lead to discoveries that will change medicine in the decades that follow. We’ll use emerging tools, methods, and models to make new discoveries and spur the translation of basic science into groundbreaking treatments and therapies.

CZI’s work in science includes grantmaking programs, open-source software development, and close collaboration with the Chan Zuckerberg Biohub Network. The CZ Biohub Network includes the San Francisco, Chicago, and New York Biohubs as well as the Chan Zuckerberg Imaging Institute. CZI also collaborates with institutional partners like the Kempner Institute for the Study of Natural & Artificial Intelligence at Harvard University. Join us in accelerating science.

The AI/ML team is funding and building one of the largest computing systems dedicated to nonprofit life science research in the world. This new effort will provide the scientific community with access to predictive models of healthy and diseased cells, which will lead to groundbreaking new discoveries that could help researchers cure, prevent, or manage all diseases by the end of this century.

The Opportunity

As a Senior/Staff Research Scientist on the AI/ML team you will conduct original research in developing state-of-the-art methods in artificial intelligence and machine learning to solve important problems in the life sciences aligned with CZI’s mission. The era of big data in biology is upon us, driven by advancements in high-throughput measurement techniques, generating vast amounts of rich multimodal data. You will work as part of a diverse team of AI scientists and engineers leveraging large multimodal datasets to build foundation models that advance both the state-of-the-art in AI as well as our understanding of biological systems. You will also have the opportunity to work on aspects of AI for scientific discovery to build systems that embed AI systems deeply into the process of proposing and generating new scientific insights and reify existing ones into scalable systems.

You will have the opportunity to work closely with teams of scientists, computational biologists, and engineers within CZI and to collaborate with CZI grantees, CZ institutes, and other external labs and organizations. Your work will inspire and enhance the production and analysis of datasets by CZ teams and collaborators.

What You’ll Do

• Conduct original research in the area of generative multimodal modeling, large language models (LLMs), diffusion models, probabilistic reasoning and causality/causal representation learning as it applies to fundamental problems in AI for advancing the sciences.
• Build, train, and evaluate multimodal foundation models utilizing CZI’s 1000xH100 GPU compute cluster and distributed training infrastructure.
• Work with a diverse range of multimodal and biological data types, including multi-omics data, cell/tissue images, human specimen/cohort data, cryoET tomography, scientific literature, and more.
• Advance the community standards for dissemination, presentation, and evaluation of computational approaches to core scientific problems.
• Contribute to the scientific community through publishing papers, blog posts, open source code, and attending conferences in machine learning and the life sciences.

What You’ll Bring

• Enjoy working in a highly interactive and cross-functional collaborative environment with a diverse team of colleagues and partners.
• Have a PhD or Masters in machine learning, computer science, math/statistics or a related field or equivalent industry experience.
• Have at least 5-8 years of experience developing and applying AI/ML methods in industry and/or academia.
• Have demonstrated experience building and training deep learning/generative models, ideally in a distributed/multi-node environment.
• Experience working with, processing, and analyzing large datasets and building data pipelines for model training.
• A good working knowledge of Python-based ML libraries and frameworks such as PyTorch, Jax, Pyro, NumPy, and Pandas.
• Have the ability to work independently and as part of a team, and have excellent communication and interpersonal skills.
• Have a proven track record of relevant research publications, preprints, or software packages.
• An appetite for turning scientific problems into reproducible, rigorously engineered systems based on quantitative evaluation
• Enthusiasm about open science and helping usher in the age of generative AI for advancing science

How to Apply

Job Types: Full-Time. Salaries: 100,000 and above.

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