Lab Partnering Service Discovery
Use the LPS faceted search filters, or search by keywords, to narrow your results.

Bert de Jong leads the Computational Chemistry, Materials, and Climate Group, which advances scientific computing by developing and enhancing applications in key disciplines, as well as developing tools and libraries for addressing general problems in computational science.
de Jong is the director of the LBNL Quantum Algorithms Team QAT4Chem, the team director of the Accelerated Research for Quantum Computing (ARQC) Team AIDE-QC, both funded by DOE ASCR, focused on developing software stacks, algorithms, and computer science and applied mathematics solutions for chemical sciences and other fields on near-term quantum computing devices. He is also a co-PI on the ARQC team FAR-QC (led out of Sandia). He is also part of LBNL’s quantum testbed, developing superconducting qubits. He is the LBNL lead for the Basic Energy Sciences Quantum Information Sciences project (led out of PNNL), where he is focusing on new approaches for encoding wave functions and embedding quantum systems. In addition, he is a co-PI on an LBNL led HEP funded quantum information science projects.
de Jong is a co-PI within the DOE ASCR Exascale Computing Project (ECP) as the LBNL lead for the NWChemEx effort, contributing to the development of an exascale computational chemistry code. He is the LBNL lead for the Basic Energy Sciences SPEC Computational Chemistry Center (led out of PNNL), where he is working on reduced scaling MCSCF and beyond GW approaches for molecules.
He leads an LBNL funded effort on machine learning for chemical sciences, focused on developing deep learning networks (GANs and autoencoders) for the prediction of structure-function relationships and its inverse, with a demonstrating in mass spectrometry. As part of this effort, his team developed the ML4Chem Python package.
Areas of expertise: software and algorithms for near-term quantum computing devices, machine learning, supercomputing, computational chemistry.


Lawrence Berkeley National Laboratory (Berkeley Lab), a U. S. Department of Energy Office of Science national lab managed by the University of California, delivers science solutions to the world â solutions derived from hundreds of patented and patent pending technologies plus scores of copyrighted software tools and published, peer-reviewed manuscripts.
Berkeley Lab has more than one hundred cutting-edge research projects using AI to find new scientific solutions to national problems. Through this effort, computer scientists, mathematicians, and domain scientists are collaborating to turn burgeoning datasets into scientific insights. Visit Berkeley Labâs Machine Learning for Science site for more information.
Berkeley Labâs advanced materials expertise is applied to innovation in batteries and other energy storage technologies, semiconductors, and photovoltaics. Additional energy-related areas of expertise include grid modernization and security, bio-based fuels and chemicals and building energy and demand response. Several National User Facilities are available for collaborative engagement: the Advanced Light Source, Molecular Foundry, National Energy Research Scientific Computing Center (NERSC), Energy Sciences Network, and the Joint Genome Institute. Other specialized facilities include FLEXLAB for building energy research and the Advanced Biofuels Process Demonstration Unit.
Ernest Orlando Lawrence, the lab's founder, believed team science yielded the greatest discoveries. That belief is reflected today in interdisciplinary teams and collaborative projects connecting Berkeley Lab, industry, and other research organizations. Berkeley Lab's Intellectual Property Office, connects industry partners with lab innovations and unique facilities to enable lab-to-market transition.

- Basic science: seeks to understand how nature works. This research includes experimental and theoretical work in materials science, physics, chemistry, biology, high-energy physics, and mathematics and computer science, including high performance computing.
- Applied science and engineering helps to find practical solutions to society’s problems. These programs focus primarily on energy resources, environmental management and national security.
Andy Mounce has research experience in condensed matter physics, semiconductor qubits, nitrogen vacancy magnetometry, and defects in wide band gap semiconductors. His expertise includes utilizing quantum information science techniques for understanding basic properties of quantum materials and quantum information relevant materials, such as superconductors, strongly correlated electronic materials, magnetic materials, and topological phases in materials. These techniques include cryogenic amplification, optically detected magnetic resonance, nitrogen vacancy detected magnetometry, photoluminescence, and bulk spin-resonance. Additionally, he is using machine learning in image analysis techniques, such as compressive sensing and neural networks, to both optimize experimental implementations and analysis.



He is the facility director for Nanofabrication at the Molecular Foundry, a DOE national user facility for nanomaterials fabrication and research located at Berkeley Lab. He applies his experience in nanophotonics and plasmonics fabrication and characterization to the development of new lithographic tools and processes. He collaborates with industry partners and fellow researchers to advance nanofabrication, thin film deposition, and electron beam lithography technologies, among others.
Areas of expertise: nanoscience, new materials, quantum, electronics/semiconductors, micro-nano-fabrication, nanodevices

Thomas Schenkel is a physicist and senior scientist at Lawrence Berkeley National Laboratory, where he is the interim Director of the Accelerator Technology and Applied Physics Division (http://atap.lbl.gov/). Thomas received his Ph.D. in physics from the Goethe University in Frankfurt. Following time as a postdoc at Lawrence Livermore National Laboratory, he joined Berkeley Lab. His research interests include novel accelerator concepts, materials far from equilibrium, exploration of fusion processes, and spin qubit architectures. Thomas also teaches a graduate course on particle accelerators at UC Berkeley.
Thomas worked on variations of time-of-flight mass spectrometry to characterize the environment of bio-molecules as a postdoc. This theme has now come up in the current Covid-19 crisis with new ideas for mass spectrometry and imaging of viruses in droplets.
COVID-19-related research: "Laser, Biosciences Researchers Combine Efforts to Study Viruses in Droplets"
Areas of expertise: accelerators, fusion, lasers, quantum, spin qubits

Irfan Siddiqi received his AB (1997) in chemistry & physics from Harvard University. He then went on to receive a PhD (2002) in applied physics from Yale University, where he stayed as a postdoctoral researcher until 2005. Irfan joined the physics department at the University of California, Berkeley in the summer of 2006. In 2006, Irfan was awarded the George E. Valley, Jr. prize by the American Physical Society for the development of the Josephson bifurcation amplifier. In 2007, he was awarded the Office of Naval Research Young Investigator Award, the Hellman Family Faculty Fund, and the UC Berkeley Chancellor’s Partnership Faculty Fund.
His group, the Quantum Nanoelectronics Laboratory, investigates the quantum coherence of various condensed matter systems ranging from microscopic nanomagnets such as single molecule magnets to complex macroscopic electrical circuits. To measure the electric and magnetic properties of these quantum systems, they are developing novel microwave frequency quantum-noise-limited amplifiers based on superconducting Josephson junctions formed by both oxide tunnel barriers and carbon nanotube weak links. Current topics of research include the dependence of quantum coherence on system complexity, the non-equilibrium quantum statistical mechanics of non-linear oscillators, the quantum coherence of single molecules, and topological architectures for maximum coherence in superconducting circuits.
Areas of expertise: quantum computing, condensed matter physics, superconducting qubits, quantum limited amplifiers, quantum circuits
.png)