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.
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.
The... more
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.
BIDS Data Science Fellowship Program
The BIDS Data Science Fellowship Program is a 2-year research training program open to postdocs (and in some cases, late-stage graduate students) at UC Berkeley, LBNL or UCSF, who are dedicated to advancing data science and undertaking innovative, cross-disciplinary data-intensive research.... 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
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 provide 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... more
Forums
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.
'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
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
BIDS-BCHSI Research Xchange Forum
The BIDS-BCHSI Research Xchange Forum will be launched in October 2020 as an open discussion platform for the interdisciplinary exchange of ideas and research projects at the intersection of healthcare and data science, enabling participants to support the development, and research of our... more
Computational Social Science Forum
The Computational Social Science Forum provides an informal setting for the interdisciplinary exchange of ideas and scholarship at the intersection of social science and data science. Our goal is to improve computational social science research, support the development and research of our members,... more
Machine Learning and Science Forum
The Machine Learning and Science Forum (formerly the Berkeley Statistics and Machine Learning Forum) was launched in Spring 2018 and currently meets biweekly (during the spring and fall semesters) to discuss current applications across a wide variety of research domains in the physical sciences and... more