BIDS training programs reflect our commitment to augment degree programs and provide valuable, accessible resources that expand collaboration opportunities for the campus community.

Cross Domain Initiatives (XDs)

BIDS’ XDs are cross-disciplinary research communities working together to identify common principles, algorithms and tools to advance research and break down the boundaries between domains, and to foster exchange and new collaborations among like-minded researchers.
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GraphXD - Graphs Across Domains

GraphXD connects scientists, researchers, and theorists interested in graphs from a variety of fields. Inspired by TextXD and ImageXD, GraphXD is organized by Berkeley Institute for Data Science (BIDS) fellows and is open to the campus community.
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ImageXD - Images Across Domains

Incredible advances are being made in image processing techniques, tools, and sampling modalities which, together with an increased accessibility to modern imaging equipment, has made image data ubiquitous across many fields, with scales ranging from microscopy to radio astronomy.   ImageXD... more
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TextXD - Text Analysis Across Domains

TextXD brings together researchers from across a wide range of disciplines, who work with text as a primary source of data, whether they identify as computer, social, data, or information scientists, including linguists. We work to identify common principles, algorithms and tools to advance text-... more

Fellowship Programs

BIDS fellowship programs for postdoctoral and graduate student researchers cross boundaries in fields ranging from astrophysics, biostatistics, and hydrology, to financial modeling, machine learning, social welfare, and the health sciences.
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BIDS Data Science Fellowship Program

The BIDS Data Science Fellows Program is a 2-year research and training fellowship open to postdocs (and in some disciplines, such as the humanities and social sciences, late-stage graduate students) at UC Berkeley, LBNL and UCSF, who are dedicated to advancing data science, undertaking... more

Computational Social Science Training Program

The UC Berkeley Computational Social Science Training Program (CSSTP) trains predoctoral students representing a variety of degree programs and expertise areas in the social sciences, including demography, public health, public policy, social epidemiology, social welfare, and sociology. Fellows... more
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Innovate For Health

The Innovate For Health program was initiated in June 2019 as a collaboration between BIDS at UC Berkeley, the Bakar Computational Health Sciences Institute (BCHSI) at UCSF, and Janssen Research & Development, LLC (part of the Janssen Pharmaceutical Companies of Johnson & Johnson),... more

Internship Programs

BIDS internships augment the Berkeley undergraduate research experience by providing engaging opportunities for undergraduate students representing a wide variety of academic disciplines.

BIDS Undergraduate Internship Program

BIDS Undergraduate Internships provides a variety of engaging data science research opportunities through UC Berkeley's Undergraduate Research Apprentice Program (URAP). BIDS Data Science Fellows, Senior Fellows, and Staff mentors enlist undergraduate students to help design and implement... more


BIDS Forums are interdisciplinary discussion groups addressing timely topics and information, offered in an informal setting, and open to our wider community, including all interested members of the UC Berkeley, UCSF, LBL and LLNL communities.
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'Information and Uncertainty in Data Science' Discussion Forum

The 'Information and Uncertainty in Data Science' Discussion Forum is a forum for open inquiry and discussion about a wide range of recurring data science fundamentals, including information, uncertainty, entropy, bits, probability, machine learning, generalization, and others. The group... more
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Best Practices in Data Science

The BIDS Best Practices in Data Science discussion series, which launched in Spring 2019, meets to synthesize participants' experiences working in the field of data science, discern how data science practices can be done well, and discover how to improve upon lessons-learned. Topics... more
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Machine Learning and Science Forum

The Machine Learning and Science Forum (formerly the Berkeley Statistics and Machine Learning Forum) meets biweekly to discuss current applications across a wide variety of research domains in the physical sciences and beyond. Hosted by UC Berkeley Physics Professor and BIDS Senior Fellow Uros... more