18 Postdoctoral Fellowship at Lawrence Berkeley National Laboratory, California, United States

Lawrence Berkeley National Lab’s (LBNL) Energy Storage & Distributed Resources Division has an opening for a Postdoctoral Fellow to join the team.

In this exciting role, you will conduct research in the area of solid-state batteries in the Battery Materials Research Program at Lawrence Berkeley National Laboratory. Working to demonstrate, analyze, and improve fabrication processes for ceramic electrolyte layer and electrolyte/cathode bilayer structures, and assess processing routes for fabrication of solid state batteries. This will include powder processing, sintering, cell fabrication and testing, mechanical testing, and diagnosis of performance-limiting and cycling-limiting phenomena. Primary focus points will be LLZO layer fabrication, cathode/electrolyte compatibility and bilayer architecture optimization. You will interact with global leaders in battery, SOFC, and ceramic electrochemical device technology.

Lawrence Berkeley National Lab’s (LBNL) Physics Division has an opening for a Postdoctoral Fellow to join the team.

In this exciting role, you will contribute to the detector commissioning, software development, data analysis, and R&D activities for the Muon to Electron Conversion  experiment (Mu2e). This work includes assisting with installation and commissioning of the Mu2e detector at Fermilab.

In this exciting role, you will conduct fundamental and applied research in sparse computations related to matrices, graphs, hypergraphs, simplicial complexes, artificial intelligence and tensors.

What You Will Do:

• Perform fundamental research in sparse matrix, sparse tensor, and sparse network algorithms.
• Design parallel algorithms for sparse computations in one or more of the three broad domains listed above.
• Implement parallel algorithms for HPC systems.
• Gain familiarity with scientific applications and scientific AI workloads involving sparse computations.
• Publish and present research results in high-impact journals and top conferences in one or more of the following areas: parallel computing, graph algorithms, sparse matrix computations, computational topology, geometric learning.

In this exciting role, you will develop innovative optimization models in the context of distribution and transmission grid investment and planning, unit commitment and economic dispatch problems. These models will be developed within multiple projects funded by the US Department of Energy.and converted into tools that can be used by the power system industry, academia or policy/regulatory entities.

Included in the Grid Integration Group, the Grid Planning and Economics team develops models and software solutions to support decisions around power systems planning, economics as well as electricity markets and policy.

This is an exciting opportunity for an early-career researcher to lead cutting-edge work in biomimetic polypeptoid surface functionalization, with applications in Extreme Ultraviolet Lithography (EUVL) and heterogeneous integration. The successful candidate will conduct interdisciplinary research across cleanroom nanofabrication, biomolecular self-assembly, and advanced imaging, leveraging state-of-the-art facilities at LBNL. This role offers a unique chance to engage in high-profile, DOE-funded collaborations with leading experts through the Center for High Precision Patterning Science (CHiPPS) and the Microelectronics Energy Efficiency Research Center for Advanced Technologies (MEERCAT).

The successful candidate will be based at the Molecular Foundry, a world-renowned research hub dedicated to nanoscale science, where they will work in a highly collaborative and mentorship-driven environment. This position provides opportunities for professional growth, networking with top-tier scientists, and publishing in top-rated scientific journals while contributing to groundbreaking advancements in nanofabrication and biomolecular engineering.

Come join Lawrence Berkeley National Lab’s (LBNL) Advanced Light Source (ALS) Division as an X-ray Optics and Machine Learning Postdoc! You will work on the forefront of scientific breakthroughs with the DREAM beam project and the ALS Computing team. This groundbreaking initiative leverages machine learning for automated alignment and cutting-edge x-ray adaptive optics to shape coherent x-ray wavefronts with nanometer precision, unlocking new possibilities for transformative research. If you’re passionate about innovation, machine learning, and collaborative science, this is your chance to make a mark at the forefront of x-ray technology!

The Advanced Light Source is a U.S. Department of Energy (DOE) Office of Science national scientific user facility whose excellent scientific reputation, expert staff, and capabilities in the soft x-ray, hard x-ray, and infrared regimes attract about 1,600 academic and industrial users each year in disciplines spanning physical, chemical, materials, biological, energy, and Earth sciences. It is one of five Berkeley Lab user facilities that serve a combined 15,000 users annually. The co-location of these user facilities – including the Molecular Foundry Nanoscale Science Research Center and the NERSC scientific computing center, as well as Berkeley Lab’s outstanding programs in materials and chemical sciences, among others – offers a prime environment for collaborative science. The ALS has been a global leader in soft x-ray science for more than two decades and is currently undergoing a large-scale upgrade (ALS-U) that will endow the facility with state-of-the-art x-ray capabilities. It’s an exciting time to join our team!

Lawrence Berkeley National Lab’s (LBNL) NERSC Division has an opening for a NESAP Machine Learning Postdoctoral Fellow to join the team.
In this exciting role, you will be a part of a multidisciplinary team composed of computational and domain scientists working together to develop machine learning approaches that run on the Perlmutter and future NERSC-10 system and produce mission-relevant science that pushes the limits of HPC. This position will carry out these efforts in collaboration with a project PI and team members, with the support of NERSC and vendor staff. 

NESAP has established a track record of enabling its Postdocs to pursue careers in machine learning, data science, HPC, and scientific computing both in industry and at national labs

The Lawrence Berkeley National Lab’s (LBNL) Atomic, Molecular and Optical Sciences (AMOS) group of the Chemical Sciences Division is seeking a Postdoctoral Researcher to  explore the ultrafast electronic and nuclear dynamics of molecules using cutting-edge extreme ultraviolet (XUV) spectroscopy.

The AMOS group seeks to answer fundamental questions in atomic, molecular, and chemical sciences by employing existing and currently emerging tools such as free electron lasers, laboratory-based extreme ultraviolet ultrafast laser sources, synchrotrons, electron beams, which are coupled with advanced electron, ion, and photon detection techniques. Combining these with state-of-the-art theory, we investigate fundamental chemistry and physics in small molecular systems over a broad range of time scales and energies. 

This position offers the opportunity to work at the forefront of ultrafast science, leveraging state-of-the-art laser systems, synchrotrons, and free electron lasers to investigate fundamental chemical and physical processes. You will join a collaborative research environment, working alongside leading scientists and contributing to groundbreaking discoveries.

Lawrence Berkeley National Lab’s (LBNL) Molecular Biophysics and Integrated Bioimaging Division (MBIB) has an opening for a Postdoctoral Fellow in XFEL Crystallography. This role is an exciting opportunity to contribute to cutting-edge research in structural biology by developing advanced computational methods, applying machine learning, and collaborating with leading scientists at national laboratories and light source facilities.

You will be part of a multidisciplinary team advancing time-resolved crystallography, diffuse scattering, and single-particle diffraction, helping to push the boundaries of structural biology at the Linac Coherent Light Source (LCLS). With the anticipated petabyte-scale datasets generated from this research, you will have the opportunity to work closely with NERSC (National Energy Research Scientific Computing Center) and leverage Exascale computing and GPU acceleration to solve complex computational challenges.

This position is ideal for candidates looking to gain hands-on experience with high-performance computing, contribute to novel algorithm development, and make an impact in structural biology, computational research, and light source facilities.

Lawrence Berkeley National Lab’s (LBNL) Energy Storage & Distributed Resources Division has an opening for a Battery Cathode Postdoctoral Fellow to join the team.

In this exciting role, you will work in the Energy Storage and Distributed Resources Division. You will support the research programs in the Electrochemistry Group aiming to develop next-generation batteries for use in electric vehicles. You will work with dynamic teams in multi-organizational consortia and carry out research activities focusing on synthesis, characterization and optimization of advanced cathode materials for rechargeable lithium-ion batteries.

The Energy Geosciences Division at Lawrence Berkeley National Laboratory has an opportunity for a postdoc who will support ongoing projects in the area of basin-scale geological CO2 storage. You will mainly work on modeling basin-scale coupled fluid transport, poroelasticity and geomechanical processes for assessing and optimizing strategies to improve basin-scale storage capacity and security. The purpose of the position is to contribute to our group’s efforts in developing new modeling capabilities and to apply existing models that may involve carrying out simulations on high-performance computing platforms. Candidates should have a solid knowledge of flow and transport in porous and fractured subsurface media, extensive experience in numerical modeling and programming involving coupled multi-physics processes, and excellent understanding of and vision for tackling a broad range of challenging subsurface problems, such as multiphase flow and geomechanics. Candidates should have a demonstrated ability to publish their research in top journals.

Berkeley Lab’s (LBNL) Biological Systems and Engineering (BSE) Division has an opening for a Postdoctoral Fellow to join the Quantitative Modeling Group led by Héctor García Martín to develop machine learning algorithms, mechanistic models, data science pipelines, and automated workflows to design cells to produce renewable products and combat climate change. You will have the opportunity to design cells to a specification, bring synthetic biology to its full potential, and enable self-driving labs.  

In this exciting role, you will work as part of a collaborative team to integrate microbial phenotypic data (e.g. fluxomics, transcriptomics, proteomics, metabolomics) into quantitative computational models able to predict and explain the outcomes of bioengineering interventions. You will work closely with an interdisciplinary team of bench scientists, automation engineers, and software developers in devising methods for high-throughput data collection and analysis for feedback into experimental design, as part of the Agile BioFoundry and the Joint BioEnergy Institute.

(18) Postdoctoral Fellowship Position

Postdoc Fellowship Position summary/title: DESI Operations Postdoctoral Fellow

Deadline : Open Until Filled

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About Lawrence Berkeley National Laboratory, California, United States – Official Website

Lawrence Berkeley National Laboratory (LBNL) is a federally funded research and development center in the hills of Berkeley, California, United States. Established in 1931 by the University of California (UC), the laboratory is sponsored by the United States Department of Energy and administered by the UC system. Ernest Lawrence, who won the Nobel prize for inventing the cyclotron, founded the Lab and served as its Director until his death in 1958. Located in the Berkeley Hills, the lab overlooks the campus of the University of California, Berkeley.