Leveraging Machine Learning to Accelerate Breakthroughs for Climate Change
Imagine a technology that could remove planet-warming emissions from smokestacks, extract moisture in the air to make drinking water and transform carbon dioxide into clean fuels and other useful substances.
The Bakar Institute of Digital Materials for the Planet (BIDMaP) aims to speed up the development of reticular chemistry and modular structures for achieving cost-efficient, easily deployable ultra-porous metal-organic frameworks (MOFs) and covalent organic frameworks (COFs). These programs will help limit and address the impacts of climate change and extend to downstream technologies like conversion of CO2 to clean fuels, biodegradable polymers, enzymes, and pharmaceuticals.
BIDMaP brings together top computation and machine learning experts with chemistry and other physical science researchers to exploit the vast potential these reticular structures have in achieving clean air, clean energy, and clean water, see here for the official BIDMaP announcement.
MOFs are crystalline structures in which a combination of multi-metal units and organic linkers are stitched together by strong bonds to make frameworks encompassing ultra-high surface areas (up to 7,000 square meters per gram of MOF material), folded and compacted into tiny spaces. Each of the more than 100,000 frameworks in existence can selectively attract, filter, store or release specific molecules like carbon dioxide and water, operating in different environments and with high precision. COFs are yet another class of ultra-porous crystals made entirely from strongly bonded organic molecules with no metals; their versatility offers another frontier in applications for electronics and climate-related catalytic conversions of carbon dioxide.
Please return to this page for more information in the near future. All immediate BIDMaP inquiries can be emailed to us at bidmap@berkeley.edu.
Faculty Leadership
Christian Borgs
Director
Omar Yaghi
Co-director and Chief Scientist
Affiliated Faculty
Jennifer Chayes
Associate Provost, Division of Computing, Data Science and Society; Dean of the School of Information
Felix Fischer
Associate Professor of Chemistry, College of Chemistry
Joseph Gonzalez
Associate Professor, Electrical Engineering and Computer Sciences
Solomon Hsiang
Chancellor's Professor of Public Policy, The Goldman School of Public Policy
Aditi Krishnapriyan
Assistant Professor, Electrical Engineering and Computer Sciences
Alessandra Lanzara
Professor, Charles Kittel Chair in Physics, Department of Physics
Jennifer Listgarten
Professor, Electrical Engineering and Computer Sciences; Center for Computational Biology
Fernando Perez
Associate Professor, Department of Statistics
Kristin Persson
Professor, Materials Science & Engineering; Director of the Molecular Foundry; Director of the Materials Project; Faculty Staff Scientist at Lawrence Berkeley National Lab
Peidong Ying
Director, Kavli Energy NanoScience Institute (ENSI); Professor, College of Chemistry
Katherine Yelick
Vice Chancellor for Research
Interim Staff
Adrian Hill
Executive Director for Interdisciplinary Initiatives, Division of Computing, Data Science, and Society
Call for BIDMaP Emerging Scholars
Postdoctoral Fellowships in Climate Change, Machine Learning and Advanced Materials
Are you interested in working at the interface of machine learning and climate change?
The BIDMaP Emerging Scholars Program is accepting fellowship applications from recent PhDs
in basic science or data science fields interested in working at the interface of machine learning,
chemistry (or other natural sciences), and climate change.
The Bakar Institute of Digital Materials for the Planet (BIDMaP) is a new institute at UC Berkeley, bringing together machine learning and data science with the natural sciences to address one of society’s most urgent challenges: climate change. BIDMaP is focused on developing new techniques in machine learning that will enhance and accelerate discovery in experimental natural sciences and development of novel materials to address climate change. BIDMaP promotes collaboration between world-renowned AI/ML experts and chemists, as well as other physical scientists, to exploit the vast potential held in metal organic frameworks (MOFs) and similar materials for clean air, clean energy, and clean water.
Candidates who are interested in exploring this cross-disciplinary area are encouraged to apply,
even if they do not have prior experience working across the target disciplines, natural sciences
and computing/statistics/AI/ML.
Eligibility
Candidates should have one of the following academic training and research profiles:
- Computing/statistics/AI/ML training, and eagerness to work with experimentalists to enable new discoveries; or
- Basic science training (experimentally or computationally trained in chemistry, physics biological sciences, or materials science), and eagerness to work with machine learning researchers to accelerate laboratory discovery with new computational techniques.
Fellows will be mentored by UC Berkeley faculty in computing/statistics/AI/ML and will collaborate with basic scientists; OR will be mentored by UC Berkeley faculty in a basic science field and collaborate with faculty in computing/statistics/AI. BIDMaP will welcome its first cohort of Emerging Scholars in 2023. For this inaugural year, fellows will be matched with a primary mentor from among BIDMaP Faculty.
Read the full fellowship description and application instructions. Questions? Email bidmap@berkeley.edu.